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Volume 1, Number 1, September, 1991David J. Hand Editorial . . . . . . . . . . . . . . . i--ii Petros Dellaportas and David Wright Positive embedded integration in Bayesian analysis . . . . . . . . . . . 1--12 Kim-Anh Do and Peter Hall Quasi-random resampling for the bootstrap . . . . . . . . . . . . . . . 13--22 Robert Fisch and Janko Gravner and David Griffeath Threshold-range scaling of excitable cellular automata . . . . . . . . . . . 23--39 T. J. Ringrose and W. J. Krzanowski Simulation study of confidence regions for canonical variate analysis . . . . . 41--46 William S. Cleveland and Eric Grosse Computational Methods for Local Regression . . . . . . . . . . . . . . . 47--62 Fergus Daly SC --- statistical calculator . . . . . 63--70 B. S. Everitt BMDP PC-90 . . . . . . . . . . . . . . . 71--73 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Zbigniew Michalewicz and Cezary Z. Janikow Genetic algorithms for numerical optimization . . . . . . . . . . . . . . 75--91 Kenneth W. Church and William A. Gale Probability scoring for spelling correction . . . . . . . . . . . . . . . 93--103 Isabella Verdinelli and Larry Wasserman Bayesian analysis of outlier problems using the Gibbs sampler . . . . . . . . 105--117 Bradley P. Carlin and Alan E. Gelfand An iterative Monte Carlo method for nonconjugate Bayesian analysis . . . . . 119--128 J. C. Wakefield and A. E. Gelfand and A. F. M. Smith Efficient Generation of Random Variates via the Ratio-of-Uniforms Method . . . . 129--133 Richard Weinberg Envisioning information . . . . . . . . 135--135 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Allan J. Macleod Performance evaluation of normal distribution software . . . . . . . . . 1--5 Uffe Kjærulff Optimal decomposition of probabilistic networks by simulated annealing . . . . 7--17 Joseph G. Hirschberg A computationally efficient method for bootstrapping systems of demand equations: A comparison to traditional techniques . . . . . . . . . . . . . . . 19--24 A. P. Dawid Applications of a general propagation algorithm for probabilistic expert systems . . . . . . . . . . . . . . . . 25--36 R. G. Cowell and A. P. Dawid Fast retraction of evidence in a probabilistic expert system . . . . . . 37--40 E. J. Bedrick Software review . . . . . . . . . . . . 41--45 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Anonymous Editorial . . . . . . . . . . . . . . . i--ii Thomas J. Lorenzen and Lynn T. Truss and W. Scott Spangler and Andrew B. Parker William T. Corpus DEXPERT: an expert system for the design of experiments . . . . . . . . . . . . . 47--54 Jan F. M. Raes Inside two commercially available statistical expert systems . . . . . . . 55--62 Wray Buntine Learning classification trees . . . . . 63--73 Katsuhiko Tsujino and Shogo Nishida A knowledge acquisition inductive system driven by empirical interpretation of derived results . . . . . . . . . . . . 75--81 Stuart L. Crawford and Robert M. Fung An analysis of two probabilistic model induction techniques . . . . . . . . . . 83--90 Judea Pearl and Thomas S. Verma A statistical semantics for causation 91--95 Padhraic Smyth Admissible stochastic complexity models for classification problems . . . . . . 97--104 Robert P. Goldman and Eugene Charniak Probabilistic text understanding . . . . 105--114 Anonymous Forthcoming papers . . . . . . . . . . . 115--115 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Patrick Royston Approximating the Shapiro--Wilk $W$-test for non-normality . . . . . . . . . . . 117--119 Mark Van Pul Simulations on the Jelinski--Moranda model of software reliability; application of some parametric bootstrap methods . . . . . . . . . . . . . . . . 121--136 R. Lockhart and T. Swartz Computing asymptotic $p$-values for EDF tests . . . . . . . . . . . . . . . . . 137--141 Gilles Celeux and Abdallah Mkhadri Discrete regularized discriminant analysis . . . . . . . . . . . . . . . . 143--151 G. P. Nason and Robin Sibson Measuring multimodality . . . . . . . . 153--160 Thomas J. DiCiccio and Michael A. Martin and G. Alastair Young Analytical approximations for iterated bootstrap confidence intervals . . . . . 161--171 Jonathan Vaughan SPSS for the Macintosh . . . . . . . . . 173--177 Anonymous Help & Contacts . . . . . . . . . . . . . ??
B. B. Van der Genugten Density of the quotient of non-negative quadratic forms in normal variables with application to the $F$-statistic . . . . 179--182 Robert Tibshirani Principal curves revisited . . . . . . . 183--190 H. Brian Hwarng and Norma Faris Hubele Boltzmann machines that learn to recognize patterns on control charts . . 191--202 Salvatore Ingrassia A comparison between the simulated annealing and the EM algorithms in normal mixture decompositions . . . . . 203--211 Michael E. Dewey Algorithms for frequency distributions: efficiency and generality comparisons 213--220 A. C. Atkinson A segmented algorithm for simulated annealing . . . . . . . . . . . . . . . 221--230 Jeffrey Jarrett SYSTAT/SYGRAPH and Micro--TSP . . . . . 231--236 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Anonymous Editorial . . . . . . . . . . . . . . . i--i Dankmar Böhning Acceleration techniques in fixed-point methods for finding percentage points 1--5 M. Delampady and I. M. L. Yee and J. V. Zidek Hierarchical Bayesian analysis of a discrete time series of Poisson counts 7--15 Murray Aitkin Posterior Bayes factor analysis for an exponential regression model . . . . . . 17--22 M. G. Schimek and K. G. Schmaranz The statistical computing environment XploRe and state-of-the-art density and regression smoothing . . . . . . . . . . 23--26 A. C. Atkinson and H.-M. Mulira The stalactite plot for the detection of multivariate outliers . . . . . . . . . 27--35 W. J. Krzanowski Permutational tests for correlation matrices . . . . . . . . . . . . . . . . 37--44 M. C. Jones and I. S. Bradbury Kernel smoothing for finite populations 45--50 Alun Thomas A note on the four-colourability of pedigrees and its consequences for probability calculations . . . . . . . . 51--54 Richard Seligson and Othar Hansson and Andrew Mayer and Gerhard Holt Book reviews . . . . . . . . . . . . . . 55--55 Anonymous Book reviews announcement . . . . . . . 58--58 Anonymous Erratum . . . . . . . . . . . . . . . . 59--59 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Anonymous Editorial . . . . . . . . . . . . . . . i--i N. H. Anderson and D. M. Titterington Cross-correlation between simultaneously generated sequences of pseudo-random uniform deviates . . . . . . . . . . . . 61--65 A. De Matteis and S. Pagnutti Long-range correlation analysis of the Wichmann--Hill random number generator 67--70 D. J. Smith and T. C. Bailey and A. G. Munford Robust classification of high-dimensional data using artificial neural networks . . . . . . . . . . . . 71--81 V. Granville and E. Schifflers Efficient algorithms for exact inference in $ 2 \times 2 $ contingency tables . . 83--87 Murray Aitkin and Camil Fuchs An analysis of models for the dilution and adulteration of fruit juice . . . . 89--99 Tony Dusoir Software review . . . . . . . . . . . . 101--102 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Olcay Arslan and Patrick D. L. Constable and John T. Kent Domains of convergence for the EM algorithm: a cautionary tale in a location estimation problem . . . . . . 103--108 Purushottam W. Laud and Paul Ramgopal and Adrian F. M. Smith Random variate generation from $D$-distributions . . . . . . . . . . . 109--112 Ali S. Hadi and Hans Nyquist Further theoretical results and a comparison between two methods for approximating eigenvalues of perturbed covariance matrices . . . . . . . . . . 113--123 Luc Devroye On random variate generation for the generalized hyperbolic secant distributions . . . . . . . . . . . . . 125--134 M. C. Jones Simple boundary correction for kernel density estimation . . . . . . . . . . . 135--146 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Paul C. Taylor and Bernard W. Silverman Block diagrams and splitting criteria for classification trees . . . . . . . . 147--161 R. Hatzinger and W. Panny Single and twin-heaps as natural data structures for percentile point simulation algorithms . . . . . . . . . 163--170 Adrian Bowman and Peter Foster Density based exploration of bivariate data . . . . . . . . . . . . . . . . . . 171--177 Anonymous The future of statistical research . . . 179--179 Ole E. Barndorff-Nielsen Important areas for future statistical research . . . . . . . . . . . . . . . . 181--181 John M. Chambers Greater or lesser statistics: a choice for future research . . . . . . . . . . 182--184 J. B. Copas On some important statistical problems 185--187 Bradley Efron Statistics in the 21st century . . . . . 188--190 J. C. Gower The next ten years in statistics? . . . 191--193 Jack Hibbert The need for research into the effectiveness of international statistical systems and standards . . . 194--196 Pierre Legendre Real data are messy . . . . . . . . . . 197--199 David S. Moore Statistics research: the next ten years 200--201 J. A. Nelder The most important areas of statistical research in the next ten years . . . . . 202--203 Donald B. Rubin The future of statistics . . . . . . . . 204--204 Richard L. Smith Statistics research for the next ten years . . . . . . . . . . . . . . . . . 205--208 Anonymous Help & Contacts . . . . . . . . . . . . . ??
F. G. Ball and G. F. Yeo Numerical evaluation of observed sojourn time distributions for a single ion channel incorporating time interval omission . . . . . . . . . . . . . . . . 1--12 G. Eslava and F. H. C. Marriott Some criteria for projection pursuit . . 13--20 Julian Stander and Bernard W. Silverman Temperature schedules for simulated annealing . . . . . . . . . . . . . . . 21--32 David Madigan Software review . . . . . . . . . . . . 33--39 M. C. Jones Book review . . . . . . . . . . . . . . 41--46 Anonymous Help & Contacts . . . . . . . . . . . . . ??
David J. Hand Editorial . . . . . . . . . . . . . . . 47--47 Zbigniew Michalewicz Evolutionary computation . . . . . . . . 49--50 Thomas Bäck and Frank Hoffmeister Basic aspects of evolution strategies 51--63 Darrell Whitley A genetic algorithm tutorial . . . . . . 65--85 John R. Koza Genetic programming as a means for programming computers by natural selection . . . . . . . . . . . . . . . 87--112 David B. Fogel Evolutionary programming: an introduction and some current directions 113--129 Fred Glover Genetic algorithms and scatter search: unsuspected potentials . . . . . . . . . 131--140 Zbigniew Michalewicz Non-standard methods in evolutionary computation . . . . . . . . . . . . . . 141--155 David J. Hand Book reviews . . . . . . . . . . . . . . 157--159 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Andrew Carothers and Jim Piper Computer-aided classification of human chromosomes: a review . . . . . . . . . 161--171 S. P. Brooks and B. J. T. Morgan Automatic starting point selection for function optimization . . . . . . . . . 173--177 William H. Dumouchel and Thomas P. Lane Automatic selection of the proper family for simultaneous confidence intervals 179--187 A. J. Gray Simulating posterior Gibbs distributions: a comparison of the Swendsen--Wang and Gibbs sampler methods 189--201 Bruce E. Barrett and J. Brian Gray A computational framework for variable selection in multivariate regression . . 203--212 Paul Blackwell The efficient estimation of tail probabilities for extremes of moving average processes using conditional simulation . . . . . . . . . . . . . . . 213--218 Clifford Lunneborg and David J. Hand Book review . . . . . . . . . . . . . . 219--220 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Anonymous Editorial . . . . . . . . . . . . . . . i--i J. A. Nelder The statistics of linear models: back to basics . . . . . . . . . . . . . . . . . 221--234 James E. Stafford and David F. Andrews and Yong Wang Symbolic computation: a unified approach to studying likelihood . . . . . . . . . 235--245 Denis Talay Presto: a software package for the simulation of diffusion processes . . . 247--251 J. Lyu and A. Gunasekaran Statistical analysis of a portable parallel non-linear programming algorithm . . . . . . . . . . . . . . . 253--258 Sylvia Frühwirth-Schnatter Applied state space modelling of non-Gaussian time series using integration-based Kalman filtering . . . 259--269 K. Skouras and C. Goutis and M. J. Bramson Estimation in linear models using gradient descent with early stopping . . 271--278 Jonathan J. Forster and Allan M. Skene Calculation of marginal densities for parameters of multinomial distributions 279--286 Persi Diaconis and Susan Holmes Gray codes for randomization procedures 287--302 Judith E. Zeh Software review . . . . . . . . . . . . 303--309 Wilfrid S. Kendall Book reviews . . . . . . . . . . . . . . 311--314 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Anonymous Statistical and scientific database management . . . . . . . . . . . . . . . 1--1 James C. French Introduction . . . . . . . . . . . . . . 2--2 Maurizio Rafanelli Aggregate statistical data: models for their representation . . . . . . . . . . 3--24 Frank Olken and Doron Rotem Random sampling from databases: a survey 25--42 Frank Olken and Doron Rotem Sampling from spatial databases . . . . 43--57 Abdullah Uz Tansel Query languages for statistical databases . . . . . . . . . . . . . . . 59--72 John C. Klensin When the metadata exceed the data: data management with uncertain data . . . . . 73--84 Anonymous Help & Contacts . . . . . . . . . . . . . ??
J. A. Nelder The statistics of linear models: back to basics . . . . . . . . . . . . . . . . . i--i Murray Aitkin Comments on J. A. Nelder: `The statistics of linear models: back to basics' . . . . . . . . . . . . . . . . 85--86 J. K. Lindsey The uses and limits of linear models . . 87--89 John Gower Comments on J. A. Nelder, `The statistics of linear models: back to basics' . . . . . . . . . . . . . . . . 91--92 F. A. Van Eeuwijk On the tenability of distinctions: some comments on `The statistics of linear models: back to basics' by John Nelder 93--95 Robert Rodriguez and Randall Tobias and Russell Wolfinger Comments on J. A. Nelder, `The statistics of linear models: back to basics' . . . . . . . . . . . . . . . . 97--101 Shayle R. Searle Comments on J. A. Nelder, `The statistics of linear models: back to basics' . . . . . . . . . . . . . . . . 103--107 J. A. Nelder Rejoinder to comments on `The statistics of linear models: back to basics' . . . 109--111 Murray Aitkin Probability model choice in single samples from exponential families using Poisson log-linear modelling, and model comparison using Bayes and posterior Bayes factors . . . . . . . . . . . . . 113--120 Christian P. Robert Simulation of truncated normal variables 121--125 Alice Zopp\`e Principal points of univariate continuous distributions . . . . . . . . 127--132 Petros Dellaportas Random variate transformations in the Gibbs sampler: issues of efficiency and convergence . . . . . . . . . . . . . . 133--140 F. A. Van Eeuwijk and L. C. P. Keizer On the use of diagnostic biplots in model screening for genotype by environment tables . . . . . . . . . . . 141--153 Morgan C. Wang and William J. Kennedy A self-validating numerical method for computation of central and non-central $F$ probabilities and percentiles . . . 155--163 Lenard I. Dalgleish Software review: Bootstrapping and jacknifing with BOJA . . . . . . . . . . 165--174 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Merrilee Hurn and Christopher Jennison A study of simulated annealing and a revised cascade algorithm for image reconstruction . . . . . . . . . . . . . 175--190 M. C. Denham Implementing partial least squares . . . 191--202 Henri Luchian and Daniel Stamate Answer-perturbation techniques for the protection of statistical databases . . 203--213 Mark J. Dixon and Jonathan A. Tawn A semi-parametric model for multivariate extreme values . . . . . . . . . . . . . 215--225 Bart Mertens and Tom Fearn and Michael Thompson The efficient cross-validation of principal components applied to principal component regression . . . . . 227--235 W. James Gauderman A method for simulating familial disease data with variable age at onset and genetic and environmental effects . . . 237--243 Jeffrey S. Simonoff A simple, automatic and adaptive bivariate density estimator based on conditional densities . . . . . . . . . 245--252 Peter W. F. Smith and John W. McDonald Exact conditional tests for incomplete contingency tables: estimating attained significance levels . . . . . . . . . . 253--256 Anonymous Help & Contacts . . . . . . . . . . . . . ??
A. C. Davison and D. V. Hinkley and B. J. Worton Accurate and efficient construction of bootstrap likelihoods . . . . . . . . . 257--264 K. J. Powell and T. Sapatinas and T. C. Bailey and W. J. Krzanowski Application of wavelets to the pre-processing of underwater sounds . . 265--273 Chris Harbron Heuristic algorithms for finding inexpensive elimination schemes . . . . 275--287 Rose D. Baker Two permutation tests of equality of variances . . . . . . . . . . . . . . . 289--296 Dipak K. Dey and Lynn Kuo and Sujit K. Sahu A Bayesian predictive approach to determining the number of components in a mixture distribution . . . . . . . . . 297--305 Neville Davies and Ed Dawson and Helen Gustafson and A. N. Pettitt Testing for randomness in stream ciphers using the binary derivative . . . . . . 307--310 Stephen Walker Generating random variates from $D$-distributions via substitution sampling . . . . . . . . . . . . . . . . 311--315 Renata Rotondi and Silvia Drappo A clustering method for global optimization based on the $k$-th nearest neighbour . . . . . . . . . . . . . . . 317--326 Michael Goldstein and David A. Wooff Bayes linear computation: concepts, implementation and programs . . . . . . 327--341 Martin Hazelton Improved Monte Carlo inference for models with additive error . . . . . . . 343--350 Anonymous Help & Contacts . . . . . . . . . . . . . ??
David J. Hand Editorial . . . . . . . . . . . . . . . 1--1 Ralf Östermark Separating trend and cyclical dynamics in state space models with exogenous inputs . . . . . . . . . . . . . . . . . 3--10 K. A. Froeschl A metadata approach to statistical query processing . . . . . . . . . . . . . . . 11--29 Jürgen Eichenauer-Herrmann Modified explicit inversive congruential pseudorandom numbers with power of $2$ modulus . . . . . . . . . . . . . . . . 31--36 N. M. Adams and S. P. J. Kirby and P. Harris and D. B. Clegg A review of parallel processing for statistical computation . . . . . . . . 37--49 W. J. Krzanowski A stopping rule for structure-preserving variable selection . . . . . . . . . . . 51--56 R. A. Rigby and D. M. Stasinopoulos A semi-parametric additive model for variance heterogeneity . . . . . . . . . 57--65 Russell Bradford and Alun Thomas Markov chain Monte Carlo methods for family trees using a parallel processor 67--75 P. W. Laud and A. F. M. Smith and P. Damien Monte Carlo methods for approximating a posterior hazard rate process . . . . . 77--83 C. J. Lawrence and W. J. Krzanowski Mixture separation for mixed-mode data 85--92 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Todd Ogden and Emanuel Parzen Change-point approach to data analytic wavelet thresholding . . . . . . . . . . 93--99 Mary Kathryn Cowles Accelerating Monte Carlo Markov chain convergence for cumulative-link generalized linear models . . . . . . . 101--111 Jun S. Liu Metropolized independent sampling with comparisons to rejection sampling and importance sampling . . . . . . . . . . 113--119 Murray Aitkin and Steve Finch and Nancy Mendell and Henry Thode A new test for the presence of a normal mixture distribution based on the posterior Bayes factor . . . . . . . . . 121--125 Murray Aitkin and Irit Aitkin A hybrid EM/Gauss--Newton algorithm for maximum likelihood in mixture distributions . . . . . . . . . . . . . 127--130 Bruce E. Barrett and J. Brian Gray Computation of determinantal subset influence in regression . . . . . . . . 131--138 Reza Modarres Bootstrap power of the generalized correlation coefficient . . . . . . . . 139--145 Tim Hesterberg Control variates and importance sampling for efficient bootstrap simulations . . 147--157 Andrew R. Webb An approach to non-linear principal components analysis using radially symmetric kernel functions . . . . . . . 159--168 F. M. Malvestuto Testing implication of hierarchical log-linear models for probability distributions . . . . . . . . . . . . . 169--176 W. J. Krzanowski Efficient cross-validation of principal components . . . . . . . . . . . . . . . 177--177 B. J. A. Mertens and T. Fearn and M. Thompson Efficient cross-validation of principal components applied to principal component regression . . . . . . . . . . 178--178 M. C. Jones and Catherine B. Hurley and Telba Z. Irony Book reviews . . . . . . . . . . . . . . 179--184 Anonymous Erratum . . . . . . . . . . . . . . . . 185--185 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Stephen Rowe An algorithm for computing principal points with respect to a loss function in the unidimensional case . . . . . . . 187--190 Daniel Zelterman and Chap T. Le and Thomas A. Louis Bootstrap techniques for proportional hazards models with censored observations . . . . . . . . . . . . . . 191--199 Gordon K. Smyth Partitioned algorithms for maximum likelihood and other non-linear estimation . . . . . . . . . . . . . . . 201--216 Boris Mirkin Clustering for contingency tables: boxes and partitions . . . . . . . . . . . . . 217--229 Stanislav Keprta Non-binary classification trees . . . . 231--243 Ronald Cools and Petros Dellaportas The role of embedded integration rules in Bayesian statistics . . . . . . . . . 245--250 Murray Aitkin A general maximum likelihood analysis of overdispersion in generalized linear models . . . . . . . . . . . . . . . . . 251--262 Aipore R. de Moraes and Ian R. Dunsmore Influential data points in predictive logistic models . . . . . . . . . . . . 263--268 Jeffrey S. Rosenthal Analysis of the Gibbs sampler for a model related to James--Stein estimators 269--275 P. Vounatsou and A. F. M. Smith Bayesian analysis of contingency tables: a simulation and graphics-based approach 277--287 José C. Pinheiro and Douglas M. Bates Unconstrained parametrizations for variance-covariance matrices . . . . . . 289--296 Alerto Roverato and Joe Whittaker Standard errors for the parameters of graphical Gaussian models . . . . . . . 297--302 Peter S. Craig and Allan H. Seheult Pseudo-likelihood estimation for a class of spatial Markov chains . . . . . . . . 303--311 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Dag Wedelin Efficient estimation and model selection in large graphical models . . . . . . . 313--323 Xun-Guo Lin and Alun Pope Coverage plots for assessing the variability of estimated contours of a density . . . . . . . . . . . . . . . . 325--336 S. K. Vines and W. R. Gilks and P. Wild Fitting Bayesian multiple random effects models . . . . . . . . . . . . . . . . . 337--346 R. Doallo-Biempica and B. B. Fraguela-Rodríguez and A. Quintela-Del-Río Evaluation of vectorization/parallelization techniques: application to nonparametric curve estimation . . . . . . . . . . . . 347--351 Radford M. Neal Sampling from multimodal distributions using tempered transitions . . . . . . . 353--366 Karen Chan and Alison Gray Robustness of automated data choices of smoothing parameter in image regularization . . . . . . . . . . . . . 367--377 J. N. R. Jeffers Software review . . . . . . . . . . . . 379--386 Nozer D. Singpurwalla and Robert Gentleman and Willem J. Heiser and Dibyen Majumdar Book reviews . . . . . . . . . . . . . . 387--391 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Halima Bensmail and Gilles Celeux and Adrian E. Raftery and Christian P. Robert Inference in model-based cluster analysis . . . . . . . . . . . . . . . . 1--10 Ming-Yen Cheng and Peter Hall and D. M. Titterington On the shrinkage of local linear curve estimators . . . . . . . . . . . . . . . 11--17 Pedro Larrañaga and Cindy M. H. Kuijpers and Mikel Poza and Roberto H. Murga Decomposing Bayesian networks: triangulation of the moral graph with genetic algorithms . . . . . . . . . . . 19--34 Merrilee Hurn Difficulties in the use of auxiliary variables in Markov chain Monte Carlo methods . . . . . . . . . . . . . . . . 35--44 Carla E. Brodley and Padhraic Smyth Applying classification algorithms in practice . . . . . . . . . . . . . . . . 45--56 Dani Gamerman Sampling from the posterior distribution in generalized linear mixed models . . . 57--68 Andrew Webb and Paul R. Yarnold and Robert C. Soltysik Review of ODA 1.0 optimal data analysis for DOSTM . . . . . . . . . . . . . . . 69--73 Jean Thioulouse and Daniel Chessel and Sylvain Dole'dec and Jean-Michel Olivier ADE-4: a multivariate analysis and graphical display software . . . . . . . 75--83 Anonymous Help & Contacts . . . . . . . . . . . . . ??
W. J. Krzanowski Recent trends and developments in computational multivariate analysis . . 87--99 F. M. Malvestuto and M. Moscarini Suppressing marginal totals from a two-dimensional table to protect sensitive information . . . . . . . . . 101--114 Peter Hall and Spiridon Penev and Gérard Kerkyacharian and Dominique Picard Numerical performance of block thresholded wavelet estimators . . . . . 115--124 H. M. Gustafson and E. P. Dawson and J. Dj. Goli\'c Automated statistical methods for measuring the strength of block ciphers 125--135 A. Silva Mato and A. Martín Andrés Simplifying the calculation of the $P$-value for Barnard's test and its derivatives . . . . . . . . . . . . . . 137--143 G. R. Oskrochi and R. B. Davies An EM-type algorithm for multivariate mixture models . . . . . . . . . . . . . 145--151 Bradley P. Carlin and Thomas A. Louis Bayes and Empirical Bayes Methods for Data Analysis . . . . . . . . . . . . . 153--154 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Trevor F. Cox and Kim F. Pearce A robust logistic discrimination model 155--161 Ouhong Wang and William J. Kennedy Application of numerical interval analysis to obtain self-validating results for multivariate probabilities in a massively parallel environment . . 163--171 Anne Philippe Simulation of right and left truncated gamma distributions by mixtures . . . . 173--181 Hui-May Chu and Lynn Kuo Sampling based approach for one-hit and multi-hit models in quantal bioassay . . 183--192 Luisa Franconi and Christopher Jennison Comparison of a genetic algorithm and simulated annealing in an application to statistical image reconstruction . . . . 193--207 Francesco Mola and Roberta Siciliano A fast splitting procedure for classification trees . . . . . . . . . . 209--216 Anonymous Help & Contacts . . . . . . . . . . . . . ??
M. Ostland and B. Yu Exploring quasi Monte Carlo for marginal density approximation . . . . . . . . . 217--228 M. Lavielle and E. Moulines A simulated annealing version of the EM algorithm for non-Gaussian deconvolution 229--236 Adrian Bowman and James Currall and Richard Lyall The birds and the bees: interactive graphics and problem solving in the teaching of statistics . . . . . . . . . 237--246 A. P. Dempster The direct use of likelihood for significance testing . . . . . . . . . . 247--252 Murray Aitkin The calibration of $P$-values, posterior Bayes factors and the AIC from the posterior distribution of the likelihood 253--261 M. Stone Discussion of papers by Dempster and Aitkin . . . . . . . . . . . . . . . . . 263--264 A. P. Dempster Commentary on the paper by Murray Aitkin, and on discussion by Mervyn Stone . . . . . . . . . . . . . . . . . 265--269 Murray Aitkin Reply . . . . . . . . . . . . . . . . . 271--272 Anonymous Indexes (Volume 7, 1997) . . . . . . . . 273--278 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Martin Anthony Probabilistic `generalization' of functions and dimension-based uniform convergence results . . . . . . . . . . 5--14 David J. C. Mackay and Ryo Takeuchi Interpolation models with multiple hyperparameters . . . . . . . . . . . . 15--23 Robert Tibshirani and Geoffrey Hinton Coaching variables for regression and classification . . . . . . . . . . . . . 25--33 David H. Wolpert and Emanuel Knill and Tal Grossman Some results concerning off-training-set and IID error for the Gibbs and the Bayes optimal generalizers . . . . . . . 35--54 C. W. H. Mace and A. C. C. Coolen Statistical mechanical analysis of the dynamics of learning in perceptrons . . 55--88 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Robert G. Cowell Mixture reduction via predictive scores 97--103 Stuart Coles Inference for circular distributions and processes . . . . . . . . . . . . . . . 105--113 Mary Kathryn Cowles and Jeffrey S. Rosenthal A simulation approach to convergence rates for Markov chain Monte Carlo algorithms . . . . . . . . . . . . . . . 115--124 Moody T. Chu and Nickolay T. Trendafilov On a differential equation approach to the weighted orthogonal Procrustes problem . . . . . . . . . . . . . . . . 125--133 R. Settimi and P. G. Blackwell Conditional simulation for moving average processes with discrete or continuous values . . . . . . . . . . . 135--144 Christian P. Robert and D. M. Titterington Reparameterization strategies for hidden Markov models and Bayesian approaches to maximum likelihood estimation . . . . . 145--158 D. Nilsson An efficient algorithm for finding the $M$ most probable configurations in probabilistic expert systems . . . . . . 159--173 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Jeffrey L. Solka and Edward J. Wegman and Carey E. Priebe and Wendy L. Poston and George W. Rogers Mixture structure analysis using the Akaike Information Criterion and the bootstrap . . . . . . . . . . . . . . . 177--188 David F. Andrews and James E. Stafford Iterated full partitions . . . . . . . . 189--192 Peter J. Rousseeuw and Anja Struyf Computing location depth and regression depth in higher dimensions . . . . . . . 193--203 A. T. Walden and A. Contreras Cristan Matching pursuit by undecimated discrete wavelet transform for non-stationary time series of arbitrary length . . . . 205--219 Håvard Rue and Oddvar K. Husby Identification of partly destroyed objects using deformable templates . . . 221--228 Agostino Nobile A hybrid Markov chain for the Bayesian analysis of the multinomial probit model 229--242 Claus Skaanning Jensen A simple method for finding a legal configuration in complex Bayesian networks . . . . . . . . . . . . . . . . 243--251 Edward A. Silver and Daniel Costa and Willard Zangwill Order statistics of independent identically distributed variables when the sum is known . . . . . . . . . . . . 253--265 S. P. Brooks Quantitative convergence assessment for Markov chain Monte Carlo via cusums . . 267--274 Bin Yu and Per Mykland Looking at Markov samplers through cusum path plots: a simple diagnostic idea . . 275--286 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Murray Aitkin and Marco Alfó Regression models for binary longitudinal responses . . . . . . . . . 289--307 A. Benn and R. Kulperger Massively parallel computing: a statistical application . . . . . . . . 309--318 Stephen P. Brooks and Gareth O. Roberts Convergence assessment techniques for Markov chain Monte Carlo . . . . . . . . 319--335 D. G. T. Denison and B. K. Mallick and A. F. M. Smith Bayesian MARS . . . . . . . . . . . . . 337--346 Peter Foster Exploring multivariate data using directions of high density . . . . . . . 347--355 Paul Gustafson A guided walk Metropolis algorithm . . . 357--364 Marc Kennedy Bayesian quadrature with non-normal approximating functions . . . . . . . . 365--375 Jian'an Luan and Julian Stander and David Wright On shape detection in noisy images with particular reference to ultrasonography 377--389 John W. Mcdonald and David C. Deroure and Danius T. Michaelides Exact tests for two-way symmetric contingency tables . . . . . . . . . . . 391--399 Anonymous Functional Data Analysis . . . . . . . . 401--403 Anonymous Software review . . . . . . . . . . . . 405--406 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Frank M. T. A. Busing and Erik Meijer and Rien Van Der Leeden Delete-$m$ Jackknife for Unequal $m$ . . 3--8 Angelo J. Canty and A. C. Davison Implementation of saddlepoint approximations in resampling problems 9--15 Siddhartha Chib and Bradley P. Carlin On MCMC sampling in hierarchical longitudinal models . . . . . . . . . . 17--26 C. F. De Beer and J. W. H. Swanepoel Simple and effective number-of-bins circumference selectors for a histogram 27--35 J. Eccleston and D. Whitaker On the design of optimal change-over experiments through multi-objective simulated annealing . . . . . . . . . . 37--42 Mohammed Reza Faghihi and Charles C. Taylor and Ian L. Dryden Procrustes shape analysis of triangulations of a two coloured point pattern . . . . . . . . . . . . . . . . 43--53 Sujit K. Sahu and Gareth O. Roberts On convergence of the EM algorithm and the Gibbs sampler . . . . . . . . . . . 55--64 Sylvain Sardy and Donald B. Percival and Andrew G. Bruce and Hong-Ye Gao and Werner Stuetzle Wavelet shrinkage for unequally spaced data . . . . . . . . . . . . . . . . . . 65--75 I. S. Weir and A. N. Pettitt Spatial modelling for binary data using a hidden conditional autoregressive Gaussian process: a multivariate extension of the probit model . . . . . 77--86 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Anthony Y. C. Kuk and Yuk W. Cheng Pointwise and functional approximations in Monte Carlo maximum likelihood estimation . . . . . . . . . . . . . . . 91--99 J. S. Marron and F. Udina Interactive local bandwidth choice . . . 101--110 Alan Willse and Robert J. Boik Identifiable finite mixtures of location models for clustering mixed-mode data 111--121 Anonymous Jerome H. Friedman and Nicholas I. Fisher . . . . . . . . . . . . . . . . . 123--143 Jerome H. Friedman and Nicholas I. Fisher Bump hunting in high-dimensional data 123--143 Willi Kloesgen Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 143--144 Peter J. Huber Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 144--146 Gregory Piatetsky-Shapiro Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 146--146 David W. Scott Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 146--147 A. J. Feelders Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 147--148 D. M. Titterington Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 148--149 Padhraic Smyth Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 149--150 Greg Ridgeway and Thomas Richardson and David Madigan Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 150--152 Glenn Stone Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 152--153 Chris Burges Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 153--154 Marcus Jürgens and Hans-J. Lenz Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 154--155 Daniel Lunn Discussion on the paper by Friedman and Fisher . . . . . . . . . . . . . . . . . 155--156 Anonymous Help & Contacts . . . . . . . . . . . . . ??
David J. Hand Editorial . . . . . . . . . . . . . . . 167--167 John Eccleston Guest Editorial: Computational Issues in Experimental Design . . . . . . . . . . 169--169 Leonie Burgess and Deborah J. Street An interchange algorithm for four factor orthogonal main effect plans . . . . . . 171--177 A. M. Dean and N. R. Draper Saturated main-effect designs for factorial experiments . . . . . . . . . 179--185 Jaime Delgado and Hari Iyer Search for optimal designs in a three stagenested random model . . . . . . . . 187--193 L. J. Elliott and J. A. Eccleston and R. J. Martin An algorithm for the design of factorial experiments when the data are correlated 195--201 J. A. John and E. R. Williams Partially-latinized designs . . . . . . 203--207 B. Jones and J. Wang Constructing optimal designs for fitting pharmacokinetic models . . . . . . . . . 209--218 J. L. Low and S. M. Lewis and P. Prescott Assessing robustness of crossover designs to subjects dropping out . . . . 219--227 R. J. Martin and M. C. Bursnall and E. C. Stillman Efficient designs for constrained mixture experiments . . . . . . . . . . 229--237 K. G. Russell A comparison of six methods of analysing row-column designs with inter-block information . . . . . . . . . . . . . . 239--246 Anonymous Help & Contacts . . . . . . . . . . . . . ??
A. C. Atkinson and T.-C. Cheng Computing least trimmed squares regression with the forward search . . . 251--263 G. Chan and A. T. A. Wood Simulation of stationary Gaussian vector fields . . . . . . . . . . . . . . . . . 265--268 T. Edgoose and L. Allison MML Markov classification of sequential data . . . . . . . . . . . . . . . . . . 269--278 H. M. Gustafson and E. P. Dawson and J. Dj. Goli\'c and A. N. Pettitt Methods for testing subblock patterns 279--286 James P. Hobert and Christian P. Robert and D. M. Titterington On perfect simulation for some mixtures of distributions . . . . . . . . . . . . 287--298 Murray Jorgensen A dynamic EM algorithm for estimating mixture proportions . . . . . . . . . . 299--302 Dimitris Karlis and Evdokia Xekalaki Improving the EM algorithm for mixtures 303--307 Y.-S. Shih Families of splitting criteria for classification trees . . . . . . . . . . 309--315 Thomas Lumley Review of the Stata statistical package 317--318 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Thomas S. Richardson Guest editorial . . . . . . . . . . . . 3--4 Rohan A. Baxter and Jonathan J. Oliver Finding overlapping components with MML 5--16 Hugh Chipman and Robert E. McCulloch Hierarchical priors for Bayesian CART shrinkage . . . . . . . . . . . . . . . 17--24 Tommi S. Jaakkola and Michael I. Jordan Bayesian parameter estimation via variational methods . . . . . . . . . . 25--37 P. Kontkanen and P. Myllymäki and T. Silander and H. Tirri and P. Grünwald On predictive distributions and Bayesian networks . . . . . . . . . . . . . . . . 39--54 David Maxwell Chickering and David Heckerman A comparison of scientific and engineering criteria for Bayesian model selection . . . . . . . . . . . . . . . 55--62 Padhraic Smyth Model selection for probabilistic clustering using cross-validated likelihood . . . . . . . . . . . . . . . 63--72 Chris S. Wallace and David L. Dowe MML clustering of multi-state, Poisson, von Mises circular and Gaussian distributions . . . . . . . . . . . . . 73--83 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Mark Berman Guest editorial: Image analysis . . . . 91--93 F. Murtagh and J.-L. Starck Image processing through multiscale analysis and measurement noise modeling 95--103 Edmond J. Breen and Ronald Jones and Hugues Talbot Mathematical morphology: a useful set of tools for image analysis . . . . . . . . 105--120 Dominique Jeulin Random texture models for material structures . . . . . . . . . . . . . . . 121--132 Shyam Kuttikkad and Rama Chellappa Statistical modeling and analysis of high-resolution Synthetic Aperture Radar images . . . . . . . . . . . . . . . . . 133--145 Richard M. Leahy and Jinyi Qi Statistical approaches in quantitative positron emission tomography . . . . . . 147--165 Anil K. Jain and Chitra Dorai 3D object recognition: Representation and matching . . . . . . . . . . . . . . 167--182 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Karen Chan and Andrea Saltelli and Stefano Tarantola Winding Stairs: a sampling tool to compute sensitivity indices . . . . . . 187--196 Arnaud Doucet and Simon Godsill and Christophe Andrieu On sequential Monte Carlo sampling methods for Bayesian filtering . . . . . 197--208 P. Jonathan and W. J. Krzanowski and W. V. McCarthy On the use of cross-validation to assess performance in multivariate prediction 209--229 J. T. Kent and M. Mohammadzadeh Global optimization of the generalized cross-validation criterion . . . . . . . 231--236 Duncan J. Murdoch and Jeffrey S. Rosenthal Efficient use of exact samples . . . . . 237--243 Robert Read and Lyn Thomas and Alan Washburn Estimating means when sampling gives probabilities as well as values or ``Looking a gift horse in the mouth'' 245--252 Bill Shipley A permutation procedure for testing the equality of pattern hypotheses across groups involving correlation or covariance matrices . . . . . . . . . . 253--257 Alun Thomas and Alexander Gutin and Victor Abkevich and Aruna Bansal Multilocus linkage analysis by blocked Gibbs sampling . . . . . . . . . . . . . 259--269 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Marco Alf\`o and Murray Aitkin Random coefficient models for binary longitudinal responses with attrition 279--287 O. Asparoukhov and W. J. Krzanowski Non-parametric smoothing of the location model in mixed variable discrimination 289--297 Mark J. Brewer A Bayesian model for local smoothing in kernel density estimation . . . . . . . 299--309 M. Goldstein and D. J. Wilkinson Bayes linear analysis for graphical models: The geometric approach to local computation and interpretive graphics 311--324 David J. Lunn and Andrew Thomas and Nicky Best and David Spiegelhalter WinBUGS --- a Bayesian modelling framework: Concepts, structure, and extensibility . . . . . . . . . . . . . 325--337 D. Peel and G. J. McLachlan Robust mixture modelling using the $t$ distribution . . . . . . . . . . . . . . 339--348 Brian M. Steele and David A. Patterson Ideal bootstrap estimation of expected prediction error for $k$-nearest neighbor classifiers: Applications for classification and error assessment . . 349--355 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Jamie Stafford Guest editorial . . . . . . . . . . . . 5--6 D. F. Andrews Asymptotic expansions of moments and cumulants . . . . . . . . . . . . . . . 7--16 Ruggero Bellio and Alessandra R. Brazzale A computer algebra package for approximate conditional inference . . . 17--24 Wilfrid S. Kendall Symbolic Itô calculus in AXIOM: An ongoing story . . . . . . . . . . . . . 25--35 G. Pistone and E. Riccomagno and Henry P. Wynn Gröbner bases and factorisation in discrete probability and Bayes . . . . . 37--46 James E. Stafford Using intersection matrices to identify graphical structure . . . . . . . . . . 47--55 A. I. Mcleod and B. Quenneville Mean likelihood estimators . . . . . . . 57--65 Elvezio Ronchetti and Laura Ventura Between stability and higher-order asymptotics . . . . . . . . . . . . . . 67--73 Bruce Smith and Christopher Field Symbolic cumulant calculations for frequency domain time series . . . . . . 75--82 John E. Kolassa Bounding convergence rates for Markov chains: An example of the use of computer algebra . . . . . . . . . . . . 83--87 Riccardo Gatto Symbolic computation for approximating distributions of some families of one and two-sample nonparametric test statistics . . . . . . . . . . . . . . . 89--95 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Anne Philippe and Christian P. Robert Riemann sums for MCMC estimation and convergence monitoring . . . . . . . . . 103--115 Man-Lai Tang Exact power computation for stratified dose-response studies . . . . . . . . . 117--124 Radford M. Neal Annealed importance sampling . . . . . . 125--139 Eva Cantoni and Elvezio Ronchetti Resistant selection of the smoothing parameter for smoothing splines . . . . 141--146 Fernando Tusell A permutation test for randomness with power against smooth variation . . . . . 147--154 F. M. Malvestuto A hypergraph-theoretic analysis of collapsibility and decomposability for extended log-linear models . . . . . . . 155--169 David G. T. Denison Boosting with Bayesian stumps . . . . . 171--178 S. P. Brooks On Bayesian analyses and finite mixtures for proportions . . . . . . . . . . . . 179--190 Steffen L. Lauritzen and Frank Jensen Stable local computation with conditional Gaussian distributions . . . 191--203 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Rodney Wolff Guest Editorial: Introduction . . . . . 211--212 Anthony J. Lawrance Chaos: But Not in Both Directions! . . . 213--216 Phil Diamond and Alexei Pokrovskii The Statistics of Simulating Chaos . . . 217--228 Bärbel F. Finkenstädt and Qiwei Yao and Howell Tong A Conditional Density Approach to the Order Determination of Time Series . . . 229--240 Silvia Golia and Marco Sandri A Resampling Algorithm for Chaotic Time Series . . . . . . . . . . . . . . . . . 241--255 Michael Small and Kevin Judd and Alistair Mees Testing Time Series for Nonlinearity . . 257--268 L. Mark Berliner Monte Carlo Based Ensemble Forecasting 269--275 Dominique Geégan and Rolf Tschernig Prediction of Chaotic Time Series in the Presence of Measurement Error: the Importance of Initial Conditions . . . . 277--284 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Michael G. Schimek Guest editorial: Semiparametric function estimation and testing . . . . . . . . . 291--292 Joan G. Staniswalis and Peter F. Thall An explanation of generalized profile likelihoods . . . . . . . . . . . . . . 293--298 Marlene Müller Estimation and testing in generalized partial linear models --- a comparative study . . . . . . . . . . . . . . . . . 299--309 Joan G. Staniswalis Discussion of the paper by Dr. M. Müller 311--312 Robert Kohn and Michael Smith and David Chan Nonparametric regression using linear combinations of basis functions . . . . 313--322 Birgit Grund and Jörg Polzehl Semiparametric lack-of-fit tests in an additive hazard regression model . . . . 323--335 Merrilee Hurn and Ingelin Steinsland and Håvard Rue Parameter estimation for a deformable template model . . . . . . . . . . . . . 337--346 Gavin J. Gibson and Eric Renshaw Likelihood estimation for stochastic compartmental models using Markov chain methods . . . . . . . . . . . . . . . . 347--358 Martin Crowder Corrected $p$-values for tests based on estimated nuisance parameters . . . . . 359--365 Qiwei Yao and Wenyang Zhang and Howell Tong Bootstrap estimation of actual significance levels for tests based on estimated nuisance parameters . . . . . 367--371 Umberto Amato and Anestis Antoniadis Adaptive wavelet series estimation in separable nonparametric regression models . . . . . . . . . . . . . . . . . 373--394 Anonymous Help & Contacts . . . . . . . . . . . . . ??
David J. Hand It's been great-and the future looks even better . . . . . . . . . . . . . . 5--5 R. Wayne Oldford Editorial . . . . . . . . . . . . . . . 7--7 Ronald W. Butler and Marc S. Paolella Calculating the density and distribution function for the singly and doubly noncentral $F$ . . . . . . . . . . . . . 9--16 Piero Barone and Giovanni Sebastiani and Julian Stander Over-relaxation methods and coupled Markov chains for Monte Carlo simulation 17--26 Petros Dellaportas and Jonathan J. Forster and Ioannis Ntzoufras On Bayesian model and variable selection using MCMC . . . . . . . . . . . . . . . 27--36 F. O. Bunnin and Y. Guo and Y. Ren Option pricing under model and parameter uncertainty using predictive densities 37--44 Guy P. Nason and Theofanis Sapatinas Wavelet packet transfer function modelling of nonstationary time series 45--56 G. D. Rayner and H. L. MacGillivray Numerical maximum likelihood estimation for the $g$-and-$k$ and generalized $g$-and-$h$ distributions . . . . . . . 57--75 Arnaud Doucet and Simon J. Godsill and Christian P. Robert Marginal maximum a posteriori estimation using Markov chain Monte Carlo . . . . . 77--84 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Enrique Alba and José M. Troya Improving flexibility and efficiency by adding parallelism to genetic algorithms 91--114 Ilya Molchanov and Sergei Zuyev Steepest descent algorithms in a space of measures . . . . . . . . . . . . . . 115--123 Xavier De Luna and Marc G. Genton Simulation-based inference for simultaneous processes on regular lattices . . . . . . . . . . . . . . . . 125--134 Nickolay T. Trendafilov GIPSCAL revisited. A projected gradient approach . . . . . . . . . . . . . . . . 135--145 Joseph B. Kadane and Pantelis K. Vlachos Hybrid methods for calculating optimal few-stage sequential strategies: Data monitoring for a clinical trial . . . . 147--152 Gillian Lancaster and Mick Green Latent variable techniques for categorical data . . . . . . . . . . . . 153--161 Murray Aitkin and Roberto Rocci A general maximum likelihood analysis of measurement error in generalized linear models . . . . . . . . . . . . . . . . . 163--174 Hong-Tu Zhu and Sik-Yum Lee Analysis of generalized linear mixed models via a stochastic approximation algorithm with Markov chain Monte--Carlo method . . . . . . . . . . . . . . . . . 175--183 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Christophe Croux and Gentiane Haesbroeck and Peter J. Rousseeuw Location adjustment for the minimum volume ellipsoid estimator . . . . . . . 191--200 Youngjo Lee Robust variance estimators for fixed-effect estimates with hierarchical-likelihood . . . . . . . . 201--207 Stephen M. S. Lee and Irene O. L. Wong A hybrid approach based on saddlepoint and importance sampling methods for bootstrap tail probability estimation 209--217 Guy P. Nason Choice of wavelet smoothness, primary resolution and threshold in wavelet shrinkage . . . . . . . . . . . . . . . 219--227 Yuzhi Cai and Wilfrid S. Kendall Perfect simulation for correlated Poisson random variables conditioned to be positive . . . . . . . . . . . . . . 229--243 Todd Mackenzie and Michal Abrahamowicz Marginal and hazard ratio specific random data generation: Applications to semi-parametric bootstrapping . . . . . 245--252 T. Fearn and P. J. Brown and P. Besbeas A Bayesian decision theory approach to variable selection for discrimination 253--260 Valérie Ventura Non-parametric bootstrap recycling . . . 261--273 Kian Guan Lim and Qin Xiao Computing maximum smoothness forward rate curves . . . . . . . . . . . . . . 275--279 Robert F. Phillips Least absolute deviations estimation via the EM algorithm . . . . . . . . . . . . 281--285 Darren J. Wilkinson and Stephen K. H. Yeung Conditional simulation from highly structured Gaussian systems, with application to blocking-MCMC for the Bayesian analysis of very large linear models . . . . . . . . . . . . . . . . . 287--300 Anonymous Help & Contacts . . . . . . . . . . . . . ??
I. H. Dinwoodie Algebraic Methods for Polynomial Statistical Models . . . . . . . . . . . 307--314 Kert Viele and Barbara Tong Modeling with Mixtures of Linear Regressions . . . . . . . . . . . . . . 315--330 Alan D. Hutson A Semi-Parametric Quantile Function Estimator for Use in Bootstrap Estimation Procedures . . . . . . . . . 331--338 David H. Foster Automatic repeated-loess decomposition of data consisting of sums of oscillatory curves . . . . . . . . . . . 339--351 A. N. Pettitt and I. S. Weir and A. G. Hart A Conditional Autoregressive Gaussian Process for Irregularly Spaced Multivariate Data with Application to Modelling Large Sets of Binary Data . . 353--367 David J. Allcroft and Chris A. Glasbey A Spectral Estimator of Arma Parameters from Thresholded Data . . . . . . . . . 369--376 Mary Kathryn Cowles MCMC Sampler Convergence Rates for Hierarchical Normal Linear Models: A Simulation Approach . . . . . . . . . . 377--389 R. G. Aykroyd Approximations for Gibbs Distribution Normalising Constants . . . . . . . . . 391--397 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Daniel Neuenschwander and Hansmartin Zeuner Generating random numbers of prescribed distribution using physical sources . . 5--11 Matteo Fischetti and Juan-José Salazar-González Partial cell suppression: a new methodology for statistical disclosure control . . . . . . . . . . . . . . . . 13--21 C. Croux and P. Filzmoser and G. Pison and P. J. Rousseeuw Fitting multiplicative models by robust alternating regressions . . . . . . . . 23--36 Philip D. O'Neill Perfect simulation for Reed--Frost epidemic models . . . . . . . . . . . . 37--44 S. K. Ng and G. J. McLachlan On the choice of the number of blocks with the incremental EM algorithm for the fitting of normal mixtures . . . . . 45--55 Malene Hòjbjerre Profile likelihood in directed graphical models from BUGS output . . . . . . . . 57--66 Nicholas T. Longford An alternative to model selection in ordinary regression . . . . . . . . . . 67--80 David H. Foster Automatic repeated-loess decomposition of data consisting of sums of oscillatory curves . . . . . . . . . . . 81--81 Anonymous Help & Contacts . . . . . . . . . . . . . ??
R. W. Oldford Editorial: Statistics and computing: Having an impact . . . . . . . . . . . . 87--89 John C. Liechty and Dennis K. J. Lin and James P. McDermott Single-pass low-storage arbitrary quantile estimation for massive datasets 91--100 Anthony Y. C. Kuk Automatic choice of driving values in Monte Carlo likelihood approximation via posterior simulations . . . . . . . . . 101--109 Glenn Marion and Gavin Gibson and Eric Renshaw Estimating likelihoods for spatio-temporal models using importance sampling . . . . . . . . . . . . . . . . 111--119 John E. Kolassa Algorithms for approximate conditional inference . . . . . . . . . . . . . . . 121--126 Rubén Fernández-Casal and Wenceslao González-Manteiga and Manuel Febrero-Bande Flexible spatio-temporal stationary variogram models . . . . . . . . . . . . 127--136 David A. Van Dyk and Ruoxi Tang The one-step-late PXEM algorithm . . . . 137--152 Kim Miller and Suneeta Ramaswami and Peter Rousseeuw and J. Antoni Sellar\`es and Diane Souvaine and Ileana Streinu and Anja Struyf Efficient computation of location depth contours by methods of computational geometry . . . . . . . . . . . . . . . . 153--162 Òyvind Langsrud ANOVA for unbalanced data: Use Type II instead of Type III sums of squares . . 163--167 Jonathan J. Forster and John W. McDonald and Peter W. F. Smith Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models . . . . . . . . . . . 169--177 Anne Philippe and Christian P. Robert Perfect simulation of positive Gaussian distributions . . . . . . . . . . . . . 179--186 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Paul Yau and Robert Kohn Estimation and variable selection in nonparametric heteroscedastic regression 191--208 Mark J. Brewer Discretisation for inference on normal mixture models . . . . . . . . . . . . . 209--219 Shoufan Fang and George Z. Gertner and Svetlana Shinkareva and Guangxing Wang and Alan Anderson Improved generalized Fourier amplitude sensitivity test (FAST) for model assessment . . . . . . . . . . . . . . . 221--226 Murray Aitkin and Rob Foxall Statistical modelling of artificial neural networks using the multi-layer perceptron . . . . . . . . . . . . . . . 227--239 M. C. Jones and I. Koch Dependence maps: Local dependence in practice . . . . . . . . . . . . . . . . 241--255 Dankmar Böhning The EM algorithm with gradient function update for discrete mixtures with known (fixed) number of components . . . . . . 257--265 Richard J. Bolton and David J. Hand and Andrew R. Webb Projection techniques for nonlinear principal component analysis . . . . . . 267--276 Harry Joe and John C. Nash Numerical optimization and surface estimation with imprecise function evaluations . . . . . . . . . . . . . . 277--286 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Leon Willenborg Guest editorial: Introduction . . . . . 291--293 Luisa Franconi and Julian Stander Spatial and non-spatial model-based protection procedures for the release of business microdata . . . . . . . . . . . 295--305 Silvia Polettini Maximum entropy simulation for microdata protection . . . . . . . . . . . . . . . 307--320 Jim Burridge Information preserving statistical obfuscation . . . . . . . . . . . . . . 321--327 Krishnamurty Muralidhar and Rathindra Sarathy A theoretical basis for perturbation methods . . . . . . . . . . . . . . . . 329--335 Silvia Polettini and Julian Stander A comment on ``A theoretical basis for perturbation methods'' by Krishnamurty Muralidhar and Rathindra Sarathy . . . . 337--338 Krishnamurty Muralidhar and Rathindra Sarathy A rejoinder to the comments by Polettini and Stander . . . . . . . . . . . . . . 339--342 Josep Domingo-Ferrer and Vicenç Torra Disclosure risk assessment in statistical microdata protection via advanced record linkage . . . . . . . . 343--354 Menno Cuppen and Leon Willenborg Source Data Perturbation and consistent sets of safe tables . . . . . . . . . . 355--362 Adrian Dobra and Alan F. Karr and Ashish P. Sanil Preserving confidentiality of high-dimensional tabulated data: Statistical and computational issues . . 363--370 Jerome P. Reiter Model Diagnostics for Remote Access Regression Servers . . . . . . . . . . . 371--380 Barry Schouten and Marc Cigrang Remote access systems for statistical analysis of microdata . . . . . . . . . 381--389 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Pierre L'Ecuyer and Renée Touzin On the Deng--Lin random number generators and related methods . . . . . 5--9 Paul Fearnhead Particle filters for mixture models with an unknown number of components . . . . 11--21 Paul Gustafson and Ying C. MacNab and Sijin Wen On the Value of derivative evaluations and random walk suppression in Markov Chain Monte Carlo algorithms . . . . . . 23--38 Nickolay T. Trendafilov and G. A. Watson The $ l_1 $ oblique Procrustes problem 39--51 John T. Kent and Patrick D. L. Constable and Fikret Er Simulation for the complex Bingham distribution . . . . . . . . . . . . . . 53--57 Chuhsing Kate Hsiao and Su-Yun Huang and Ching-Wei Chang Bayesian marginal inference via candidate's formula . . . . . . . . . . 59--66 Rostislav S. Protassov EM-based maximum likelihood parameter estimation for multivariate generalized hyperbolic distributions with fixed $ \lambda $ . . . . . . . . . . . . . . . 67--77 Anonymous Help & Contacts . . . . . . . . . . . . . ??
D. Waddington and R. Thompson Using a correlated probit model approximation to estimate the variance for binary matched pairs . . . . . . . . 83--90 Xin Huang and Christopher G. Small Calculating the simplex median . . . . . 91--98 David J. Gorsich and Marc G. Genton On the discretization of nonparametric isotropic covariogram estimators . . . . 99--108 Matthew A. Bognar and Mary Kathryn Cowles Bayesian inference for pairwise interacting point processes . . . . . . 109--117 Tsung I. Lin and Jack C. Lee and Huey F. Ni Bayesian analysis of mixture modelling using the multivariate t distribution 119--130 Andrey Feuerverger and Jeffrey S. Rosenthal Achieving limiting distributions for Markov chains using back buttons . . . . 131--141 Martin Wainwright and Tommi Jaakkola and Alan Willsky Tree consistency and bounds on the performance of the max-product algorithm and its generalizations . . . . . . . . 143--166 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Matt Whiley and Simon P. Wilson Parallel algorithms for Markov chain Monte Carlo methods in latent spatial Gaussian models . . . . . . . . . . . . 171--179 M. Gómez and C. Bielza Node deletion sequences in influence diagrams using genetic algorithms . . . 181--198 Alex J. Smola and Bernhard Schölkopf A tutorial on support vector regression 199--222 Efthymios G. Tsionas Bayesian inference for multivariate gamma distributions . . . . . . . . . . 223--233 Daniela De Canditiis and Theofanis Sapatinas Testing for additivity and joint effects in multivariate nonparametric regression using Fourier and wavelet methods . . . 235--249 Alan Genz Numerical computation of rectangular bivariate and trivariate normal and $t$ probabilities . . . . . . . . . . . . . 251--260 Paul Fearnhead Filtering recursions for calculating likelihoods for queues based on inter-departure time data . . . . . . . 261--266 Christophe Biernacki Initializing EM using the properties of its trajectories in Gaussian mixtures 267--279 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Ian H. Dinwoodie and Laura Felicia Matusevich and Ed Mosteig Transform methods for the hypergeometric distribution . . . . . . . . . . . . . . 287--297 Chin-Tsai Lin and Chie-Bein Chen and Wen-Hsiang Wu Fuzzy clustering algorithm for latent class model . . . . . . . . . . . . . . 299--310 Heather M. Podlich and Malcolm J. Faddy and Gordon K. Smyth Semi-parametric extended Poisson process models for count data . . . . . . . . . 311--321 José G. Dias and Michel Wedel An empirical comparison of EM, SEM and MCMC performance for problematic Gaussian mixture likelihoods . . . . . . 323--332 Sylvain Maire Polynomial approximations of multivariate smooth functions from quasi-random data . . . . . . . . . . . 333--336 Thomas C. M. Lee and Hee-Seok Oh Automatic polynomial wavelet regression 337--341 Zhihua Zhang and Kap Luk Chan and Yiming Wu and Chibiao Chen Learning a multivariate Gaussian mixture model with the reversible jump MCMC algorithm . . . . . . . . . . . . . . . 343--355 Julian J. Faraway Modeling continuous shape change for facial animation . . . . . . . . . . . . 357--363 Anonymous Help & Contacts . . . . . . . . . . . . . ??
G. H. Zhao and K. L. Teo and K. S. Chan Estimation of conditional quantiles by a new smoothing approximation of asymmetric loss functions . . . . . . . 5--11 Faming Liang Bayesian neural networks for nonlinear time series forecasting . . . . . . . . 13--29 J. Q. Shi and R. Murray-Smith and D. M. Titterington Hierarchical Gaussian process mixtures for regression . . . . . . . . . . . . . 31--41 Rechel M. Hilliam and Anthony J. Lawrance Chaos communication synchronization: Combatting noise by distribution transformation . . . . . . . . . . . . . 43--52 Òyvind Langsrud Rotation tests . . . . . . . . . . . . . 53--60 Deepak K. Agarwal and Alan E. Gelfand Slice sampling for simulation based fitting of spatial data models . . . . . 61--69 Paul Kabaila Computation of exact confidence intervals from discrete data using Studentized test statistics . . . . . . 71--78 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Idris A. Eckley and Guy P. Nason Efficient computation of the discrete autocorrelation wavelet inner product matrix . . . . . . . . . . . . . . . . . 83--92 David J. Nott and Anthony Y. C. Kuk and Hiep Duc Efficient sampling schemes for Bayesian MARS models with many predictors . . . . 93--101 Stefanos G. Giakoumatos and Petros Dellaportas and Dimitris N. Politis Bayesian analysis of the unobserved ARCH model . . . . . . . . . . . . . . . . . 103--111 M. Di Marzio and C. C. Taylor Kernel density classification and boosting: an $ L_2 $ analysis . . . . . 113--123 Paul Fearnhead Direct simulation for discrete mixture distributions . . . . . . . . . . . . . 125--133 Dong Guo and Xiaodong Wang and Rong Chen New sequential Monte Carlo methods for nonlinear dynamic systems . . . . . . . 135--147 Anonymous Help & Contacts . . . . . . . . . . . . . ??
G. Tutz and H. Binder Localized classification . . . . . . . . 155--166 Trevor Sweeting and Samer Kharroubi Application of a predictive distribution formula to Bayesian computation for incomplete data models . . . . . . . . . 167--178 Peter Schlattmann On bootstrapping the number of components in finite mixtures of Poisson distributions . . . . . . . . . . . . . 179--188 Alain Desgagné and Jean-François Angers Importance sampling with the generalized exponential power density . . . . . . . 189--196 Markus Frölich Matching estimators and optimal bandwidth choice . . . . . . . . . . . . 197--215 Murray Aitkin and Richard J. Boys and Tom Chadwick Bayesian point null hypothesis testing via the posterior likelihood ratio . . . 217--230 Abdissa Negassa and Antonio Ciampi and Michal Abrahamowicz and Stanley Shapiro and Jean-François Boivin Tree-structured subgroup analysis for censored survival data: Validation of computationally inexpensive model selection criteria . . . . . . . . . . . 231--239 Dirk V. Arnold and Hans-Georg Beyer Expected sample moments of concomitants of selected order statistics . . . . . . 241--250 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Dimitris Karlis and Loukia Meligkotsidou Multivariate Poisson regression with covariance structure . . . . . . . . . . 255--265 Peter K. Dunn and Gordon K. Smyth Series evaluation of Tweedie exponential dispersion model densities . . . . . . . 267--280 Ronald W. Butler and Andrew T. A. Wood Approximation of power in multivariate analysis . . . . . . . . . . . . . . . . 281--287 J. Roca-Pardiñas and C. Cadarso-Suárez and W. González-Manteiga Testing for interactions in generalized additive models: Application to SO$_2$ pollution data . . . . . . . . . . . . . 289--299 Jochen Einbeck and Gerhard Tutz and Ludger Evers Local principal curves . . . . . . . . . 301--313 Peter Neal and Gareth Roberts A case study in non-centering for data augmentation: Stochastic epidemics . . . 315--327 Feng Zhang and Bani Mallick and Zhujun Weng A Bayesian method for identifying independent sources of non-random spatial patterns . . . . . . . . . . . . 329--339 Sven Knoth Accurate ARL computation for EWMA-$ S^2 $ control charts . . . . . . . . . . . . 341--352 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Jon D. McAuliffe and David M. Blei and Michael I. Jordan Nonparametric empirical Bayes for the Dirichlet process mixture model . . . . 5--14 Martin J. Wolfsegger and Thomas Jaki Simultaneous confidence intervals by iteratively adjusted alpha for relative effects in the one-way layout . . . . . 15--23 Donald B. Percival and William L. B. Constantine Exact simulation of Gaussian Time Series from Nonparametric Spectral Estimates with Application to Bootstrapping . . . 25--35 Umberto Amato and Anestis Antoniadis and Marianna Pensky Wavelet kernel penalized estimation for non-equispaced design regression . . . . 37--55 Petros Dellaportas and Ioulia Papageorgiou Multivariate mixtures of normals with unknown number of components . . . . . . 57--68 Youngjo Lee and John A. Nelder Fitting via alternative random-effect models . . . . . . . . . . . . . . . . . 69--75 Marina Meila and Tommi Jaakkola Tractable Bayesian learning of tree belief networks . . . . . . . . . . . . 77--92 Jo Eidsvik and HåKon Tjelmeland On directional Metropolis--Hastings algorithms . . . . . . . . . . . . . . . 93--106 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Wolfgang Jank Efficient simulated maximum likelihood with an application to online retailing 111--124 Mike K. P. So Bayesian analysis of nonlinear and non-Gaussian state space models via multiple-try sampling methods . . . . . 125--141 Matthew A. Nunes and Marina I. Knight and Guy P. Nason Adaptive lifting for nonparametric regression . . . . . . . . . . . . . . . 143--159 Jan Poland and Marcus Hutter MDL convergence speed for Bernoulli sequences . . . . . . . . . . . . . . . 161--175 T. Bernholt and R. Fried and U. Gather and I. Wegener Modified repeated median filters . . . . 177--192 Yongtao Guan and Roland Fleißner and Paul Joyce and Stephen M. Krone Markov Chain Monte Carlo in small worlds 193--202 Paul Fearnhead Exact and efficient Bayesian inference for multiple changepoint problems . . . 203--213 Nizar Bouguila and Djemel Ziou and Ernest Monga Practical Bayesian estimation of a finite beta mixture through Gibbs sampling and its applications . . . . . 215--225 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Marco Alf\`o and Murray Aitkin Variance component models for longitudinal count data with baseline information: epilepsy data revisited . . 231--238 Cajo J. F. Ter Braak A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces . . . . . . . . . 239--249 Enrique Alba and Enrique Domínguez Comparative analysis of modern optimization tools for the $p$-median problem . . . . . . . . . . . . . . . . 251--260 Alfred Kume and Stephen G. Walker Sampling from compositional and directional distributions . . . . . . . 261--265 Kenny Y. F. Chan and Stephen M. S. Lee and Kai W. Ng Minimum variance unbiased estimation based on bootstrap iterations . . . . . 267--277 Onno Zoeter and Tom Heskes Deterministic approximate inference techniques for conditionally Gaussian state space models . . . . . . . . . . . 279--292 Barry R. Cobb and Prakash P. Shenoy and Rafael Rumí Approximating probability density functions in hybrid Bayesian networks with mixtures of truncated exponentials 293--308 Nikolaos Demiris and Philip D. O'Neill Computation of final outcome probabilities for the generalised stochastic epidemic . . . . . . . . . . 309--317 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Andrew Golightly and Darren J. Wilkinson Bayesian sequential inference for nonlinear multivariate diffusions . . . 323--338 Heikki Haario and Marko Laine and Antonietta Mira and Eero Saksman DRAM: Efficient adaptive MCMC . . . . . 339--354 Jukka Corander and Mats Gyllenberg and Timo Koski Bayesian model learning based on a parallel MCMC strategy . . . . . . . . . 355--362 Robert G. Aykroyd and Brain A. Cattle A flexible statistical and efficient computational approach to object location applied to electrical tomography . . . . . . . . . . . . . . . 363--375 A. W. Bowman and A. Pope and B. Ismail Detecting discontinuities in nonparametric regression curves and surfaces . . . . . . . . . . . . . . . . 377--390 G. J. Gibson and W. Otten and J. A. N. Filipe and A. Cook and G. Marion and C. A. Gilligan Bayesian estimation for percolation models of disease spread in plant populations . . . . . . . . . . . . . . 391--402 Anonymous Help & Contacts . . . . . . . . . . . . . ??
W. S. Kendall and J.-M. Marin and C. P. Robert Confidence bands for Brownian motion and applications to Monte Carlo simulation 1--10 David J. Hand and Wojtek J. Krzanowski and Martin J. Crowder Optimal predictive partitioning . . . . 11--21 Gopi Goswami and Jun S. Liu On learning strategies for evolutionary Monte Carlo . . . . . . . . . . . . . . 23--38 M. Bock and A. W. Bowman and B. Ismail Estimation and inference for error variance in bivariate nonparametric regression . . . . . . . . . . . . . . . 39--47 Youngjo Lee and John A. Nelder and Maengseok Noh H-likelihood: problems and solutions . . 49--55 Sinjini Mitra and Nicole A. Lazar and Yanxi Liu Understanding the role of facial asymmetry in human face identification 57--70 Adelchi Azzalini and Nicola Torelli Clustering via nonparametric density estimation . . . . . . . . . . . . . . . 71--80 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Tsung I. Lin and Jack C. Lee and Wan J. Hsieh Robust mixture modeling using the skew $t$ distribution . . . . . . . . . . . . 81--92 Loukia Meligkotsidou Bayesian multivariate Poisson mixtures with an unknown number of components . . 93--107 Radu V. Craiu and Christiane Lemieux Acceleration of the Multiple-Try Metropolis algorithm using antithetic and stratified sampling . . . . . . . . 109--120 Marc Lavielle and Cristian Meza A parameter expansion version of the SAEM algorithm . . . . . . . . . . . . . 121--130 David S. Leslie and Robert Kohn and David J. Nott A general approach to heteroscedastic linear regression . . . . . . . . . . . 131--146 Agostino Nobile and Alastair T. Fearnside Bayesian finite mixtures with an unknown number of components: The allocation sampler . . . . . . . . . . . . . . . . 147--162 Hongtu Zhu and Minggao Gu and Bradley Peterson Maximum likelihood from spatial random effects models via the stochastic approximation expectation maximization algorithm . . . . . . . . . . . . . . . 163--177 B. Ganguli and M. P. Wand Feature significance in generalized additive models . . . . . . . . . . . . 179--192 Sourabh Bhattacharya and Alan E. Gelfand and Kent E. Holsinger Model fitting and inference under latent equilibrium processes . . . . . . . . . 193--208 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Allou Samé and Christophe Ambroise and Gérard Govaert An online classification EM algorithm based on the mixture model . . . . . . . 209--218 Martin Neil and Manesh Tailor and David Marquez Inference in hybrid Bayesian networks using dynamic discretization . . . . . . 219--233 Jouni Kerman and Andrew Gelman Manipulating and summarizing posterior simulations using random variable objects . . . . . . . . . . . . . . . . 235--244 Richard J. Stevens and Trevor J. Sweeting Estimation across multiple models with application to Bayesian computing and software development . . . . . . . . . . 245--252 Woncheol Jang and Martin Hendry Cluster analysis of massive datasets in astronomy . . . . . . . . . . . . . . . 253--262 Ajay Jasra and David A. Stephens and Christopher C. Holmes On population-based simulation for static inference . . . . . . . . . . . . 263--279 Alicja Jokiel-Rokita and Ryszard Magiera Minimax estimation of a probability of success under LINEX loss . . . . . . . . 281--291 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Ir\`ene Gannaz Robust estimation and wavelet thresholding in partially linear models 293--310 James P. McDermott and G. Jogesh Babu and John C. Liechty and Dennis K. J. Lin Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation . . . . . . . . . . . 311--321 Jun Yan and Mary Kathryn Cowles and Shaowen Wang and Marc P. Armstrong Parallelizing MCMC for Bayesian spatiotemporal geostatistical models . . 323--335 Leena Choi and Brian Caffo and Charles Rohde Optimal sampling times in bioequivalence studies using a simulated annealing algorithm . . . . . . . . . . . . . . . 337--347 A. Delaigle and I. Gijbels Frequent problems in calculating integrals and optimizing objective functions: a case study in density deconvolution . . . . . . . . . . . . . 349--355 S. A. Sisson and Y. Fan A distance-based diagnostic for trans-dimensional Markov chains . . . . 357--367 Òivind Skare and Jesper Mòller and Eva B. Vedel Jensen Bayesian analysis of spatial point processes in the neighbourhood of Voronoi networks . . . . . . . . . . . . 369--379 John S. Preisser and Jamie Perin Deletion diagnostics for marginal mean and correlation model parameters in estimating equations . . . . . . . . . . 381--393 Ulrike von Luxburg A tutorial on spectral clustering . . . 395--416 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Sylvia Frühwirth-Schnatter and Regina Tüchler Bayesian parsimonious covariance estimation for hierarchical linear mixed models . . . . . . . . . . . . . . . . . 1--13 Juliana Gambini and Marta E. Mejail and Julio Jacobo-Berlles and Alejandro C. Frery Accuracy of edge detection methods with local information in speckled imagery 15--26 Dimitris Karlis and Panagiotis Tsiamyrtzis Exact Bayesian modeling for bivariate Poisson data and extensions . . . . . . 27--40 Pierre Hansen and Nenad Mladenovi\'c Complement to a comparative analysis of heuristics for the $p$-median problem 41--46 Adam M. Johansen and Arnaud Doucet and Manuel Davy Particle methods for maximum likelihood estimation in latent variable models . . 47--57 Pierre Pinson and Henrik Aa. Nielsen and Henrik Madsen and Torben S. Nielsen Local linear regression with adaptive orthogonal fitting for the wind power application . . . . . . . . . . . . . . 59--71 Peter K. Dunn and Gordon K. Smyth Evaluation of Tweedie exponential dispersion model densities by Fourier inversion . . . . . . . . . . . . . . . 73--86 Harald Binder and Gerhard Tutz A comparison of methods for the fitting of generalized additive models . . . . . 87--99 Zheng Su and Jiaqiao Hu and Wei Zhu Multi-step variance minimization in sequential tests . . . . . . . . . . . . 101--108 Anonymous Help & Contacts . . . . . . . . . . . . . ??
J.-H. Zhao and Philip L. H. Yu and Qibao Jiang ML estimation for factor analysis: EM or non-EM? . . . . . . . . . . . . . . . . 109--123 R. J. Boys and D. J. Wilkinson and T. B. L. Kirkwood Bayesian inference for a discretely observed stochastic kinetic model . . . 125--135 Marco Alf\`o and Luciano Nieddu and Donatella Vicari A finite mixture model for image segmentation . . . . . . . . . . . . . . 137--150 Paul Fearnhead Computational methods for complex stochastic systems: a review of some alternatives to MCMC . . . . . . . . . . 151--171 J.-J. Daudin and F. Picard and S. Robin A mixture model for random graphs . . . 173--183 Christian H. Weiß Statistical mining of interesting association rules . . . . . . . . . . . 185--194 Willi Sauerbrei and Norbert Holländer and Anika Buchholz Investigation about a screening step in model selection . . . . . . . . . . . . 195--208 C. J. Pérez and J. Martín and C. Rojano and F. J. Girón Efficient generation of random vectors by using the ratio-of-uniforms method with ellipsoidal envelopes . . . . . . . 209--217 P. Besbeas and B. J. T. Morgan Improved estimation of the stable laws 219--231 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Yungtai Lo A likelihood ratio test of a homoscedastic normal mixture against a heteroscedastic normal mixture . . . . . 233--240 Gerhard Koekemoer and Jan W. H. Swanepoel A semi-parametric method for transforming data to normality . . . . . 241--257 David Bremner and Dan Chen and John Iacono and Stefan Langerman and Pat Morin Output-sensitive algorithms for Tukey depth and related problems . . . . . . . 259--266 J. Q. Shi and B. Wang Curve prediction and clustering with mixtures of Gaussian process functional regression models . . . . . . . . . . . 267--283 Paul David McNicholas and Thomas Brendan Murphy Parsimonious Gaussian mixture models . . 285--296 W. González-Manteiga and M. D. Martínez-Miranda and R. Raya-Miranda SiZer Map for inference with additive models . . . . . . . . . . . . . . . . . 297--312 Ralph dos Santos Silva and Hedibert Freitas Lopes Copula, marginal distributions and model selection: a Bayesian note . . . . . . . 313--320 Riccardo Gatto Some computational aspects of the generalized von Mises distribution . . . 321--331 Ali Baharev and Sándor Kemény On the computation of the noncentral $F$ and noncentral beta distribution . . . . 333--340 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Paul Fearnhead Editorial: Special issue on adaptive Monte Carlo methods . . . . . . . . . . 341--342 Christophe Andrieu and Johannes Thoms A tutorial on adaptive MCMC . . . . . . 343--373 Yuan Ren and Yu Ding and Faming Liang Adaptive evolutionary Monte Carlo algorithm for optimization with applications to sensor placement problems . . . . . . . . . . . . . . . . 375--390 Richard Gerlach and Cathy W. S. Chen Bayesian inference and model comparison for asymmetric smooth transition heteroskedastic models . . . . . . . . . 391--408 Jonathan M. Keith and Dirk P. Kroese and George Y. Sofronov Adaptive independence samplers . . . . . 409--420 Bo Cai and Renate Meyer and François Perron Metropolis--Hastings algorithms with adaptive proposals . . . . . . . . . . . 421--433 Cajo J. F. ter Braak and Jasper A. Vrugt Differential Evolution Markov Chain with snooker updater and fewer chains . . . . 435--446 Olivier Cappé and Randal Douc and Arnaud Guillin and Jean-Michel Marin and Christian P. Robert Adaptive importance sampling in general mixture classes . . . . . . . . . . . . 447--459 Julien Cornebise and Éric Moulines and Jimmy Olsson Adaptive methods for sequential importance sampling with application to state space models . . . . . . . . . . . 461--480 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Marina I. Knight and Guy P. Nason A `nondecimated' lifting transform . . . 1--16 Debasish Roy and Geoff Nicholls and Colin Fox Imaging convex quadrilateral inclusions in uniform conductors from electrical boundary measurements . . . . . . . . . 17--26 Hee-Seok Oh and Donghoh Kim and Yongdai Kim Robust wavelet shrinkage using robust selection of thresholds . . . . . . . . 27--34 A. Berlinet and C. Roland Parabolic acceleration of the EM algorithm . . . . . . . . . . . . . . . 35--47 C. A. Glasbey Two-dimensional generalisations of dynamic programming for image analysis 49--56 T. J. Heaton Adaptive thresholding of sequences with locally variable strength . . . . . . . 57--71 Dimitris Karlis and Anais Santourian Model-based clustering with non-elliptically contoured distributions 73--83 Caroline Bernard-Michel and Laurent Gardes and Stéphane Girard Gaussian Regularized Sliced Inverse Regression . . . . . . . . . . . . . . . 85--98 Luke Akong'o Orawo and J. Andrés Christen Bayesian sequential analysis for multiple-arm clinical trials . . . . . . 99--109 Nicolas Chopin Book Review: Jim Albert: \booktitleBayesian computation with R 111--112 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Reinhard Furrer and Stephan R. Sain Spatial model fitting for large datasets with applications to climate and microarray problems . . . . . . . . . . 113--128 Djalil Chafa\"\i and Didier Concordet A new method for the estimation of variance matrix with prescribed zeros in nonlinear mixed effects models . . . . . 129--138 Hsiuying Wang Exact average coverage probabilities and confidence coefficients of confidence intervals for discrete distributions . . 139--148 Henghsiu Tsai and Kung-Sik Chan A note on the non-negativity of continuous-time ARMA and GARCH processes 149--153 E. Di Nardo and G. Guarino and D. Senato A new method for fast computing unbiased estimators of cumulants . . . . . . . . 155--165 A. Kume and S. G. Walker On the Fisher--Bingham distribution . . 167--172 Joseph Ryan G. Lansangan and Erniel B. Barrios Principal components analysis of nonstationary time series data . . . . . 173--187 D. Allingham and R. A. R. King and K. L. Mengersen Bayesian estimation of quantile distributions . . . . . . . . . . . . . 189--201 S. Saha and P. K. Mandal and Y. Boers and H. Driessen and A. Bagchi Gaussian proposal density using moment matching in SMC methods . . . . . . . . 203--208 Rosa Arboretti Giancristofaro and Stefano Bonnini and Fortunato Pesarin A permutation approach for testing heterogeneity in two-sample categorical variables . . . . . . . . . . . . . . . 209--216 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Martin L. Hazelton and Berwin A. Turlach Nonparametric density deconvolution by weighted kernel estimators . . . . . . . 217--228 Ian L. Dryden and Li Bai and Christopher J. Brignell and Linlin Shen Factored principal components analysis, with applications to face recognition 229--238 Gerhard Tutz and Jan Ulbricht Penalized regression with correlation-based penalty . . . . . . . 239--253 Pedro Delicado and Marcelo Smrekar Measuring non-linear dependence for two random variables distributed along a curve . . . . . . . . . . . . . . . . . 255--269 Colin Chen and Keming Yu Automatic Bayesian quantile regression curve fitting . . . . . . . . . . . . . 271--281 Florent Chatelain and Sophie Lambert-Lacroix and Jean-Yves Tourneret Pairwise likelihood estimation for multivariate mixed Poisson models generated by Gamma intensities . . . . . 283--301 Helen Armstrong and Christopher K. Carter and Kin Foon Kevin Wong and Robert Kohn Bayesian covariance matrix estimation using a mixture of decomposable graphical models . . . . . . . . . . . . 303--316 Chun-Xia Zhang and Jiang-She Zhang A novel method for constructing ensemble classifiers . . . . . . . . . . . . . . 317--327 C. A. McGrory and D. M. Titterington and R. Reeves and A. N. Pettitt Variational Bayes for estimating the parameters of a hidden Potts model . . . 329--340 Andrea Cerioli and Marco Riani and Anthony C. Atkinson Controlling the size of multivariate outlier tests with the MCD estimator of scatter . . . . . . . . . . . . . . . . 341--353 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Ying Yang Penalized semiparametric density estimation . . . . . . . . . . . . . . . 355--366 Juan A. Cuesta-Albertos and Antonio Cuevas and Ricardo Fraiman On projection-based tests for directional and compositional data . . . 367--380 Antonello Maruotti and Tobias Rydén A semiparametric approach to hidden Markov models under longitudinal observations . . . . . . . . . . . . . . 381--393 David J. Lunn and Nicky Best and John C. Whittaker Generic reversible jump MCMC using graphical models . . . . . . . . . . . . 395--408 Y. Fan and G. W. Peters and S. A. Sisson Automating and evaluating reversible jump MCMC proposal distributions . . . . 409--421 Eric Renshaw and Carlos Comas Space-time generation of high intensity patterns using growth-interaction processes . . . . . . . . . . . . . . . 423--437 M. S. Ridout Generating random numbers from a distribution specified by its Laplace transform . . . . . . . . . . . . . . . 439--450 Cinzia Viroli Bayesian inference in non-Gaussian factor analysis . . . . . . . . . . . . 451--463 Frédéric J. P. Richard and Adeline M. M. Samson and Charles A. Cuénod A SAEM algorithm for the estimation of template and deformation parameters in medical image sequences . . . . . . . . 465--478 Sylvia Frühwirth-Schnatter and Rudolf Frühwirth and Leonhard Held and Håvard Rue Improved auxiliary mixture sampling for hierarchical models of non-Gaussian data 479--492 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Robert Gramacy and Richard Samworth and Ruth King Importance tempering . . . . . . . . . . 1--7 F. Greselin and S. Ingrassia Constrained monotone EM algorithms for mixtures of multivariate $t$ distributions . . . . . . . . . . . . . 9--22 Giovanna Capizzi and Guido Masarotto Evaluation of the run-length distribution for a combined Shewhart--EWMA control chart . . . . . . 23--33 Arthur Charpentier and Abder Oulidi Beta kernel quantile estimators of heavy-tailed loss distributions . . . . 35--55 Nicolas Wicker Perfect sampling algorithm for small $ m \times n $ contingency tables . . . . . 57--61 Michael G. B. Blum and Olivier François Non-linear regression models for Approximate Bayesian Computation . . . . 63--73 Yong Wang Maximum likelihood computation for fitting semiparametric mixture models 75--86 Man-Lai Tang and Maozai Tian Approximate confidence interval construction for risk difference under inverse sampling . . . . . . . . . . . . 87--98 Frank Critchley and Michaël Schyns and Gentiane Haesbroeck and Cécile Fauconnier and Guobing Lu and Richard A. Atkinson and Dong Qian Wang A relaxed approach to combinatorial problems in robustness and diagnostics 99--115 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Gerhard Tutz Guest Editorial: Regularisation Methods in Regression and Classification . . . . 117--118 Peter Bühlmann and Torsten Hothorn Twin Boosting: improved feature selection and prediction . . . . . . . . 119--138 Matthias Schmid and Sergej Potapov and Annette Pfahlberg and Torsten Hothorn Estimation and regularization techniques for regression models with multidimensional prediction functions 139--150 Christine Porzelius and Martin Schumacher and Harald Binder Sparse regression techniques in low-dimensional survival data settings 151--163 Jinfeng Xu and Chenlei Leng and Zhiliang Ying Rank-based variable selection with censored data . . . . . . . . . . . . . 165--176 Rudolf Beran and Lutz Dümbgen Least squares and shrinkage estimation under bimonotonicity constraints . . . . 177--189 Brian D. Marx and Paul H. C. Eilers and Jutta Gampe and Roland Rau Bilinear modulation models for seasonal tables of counts . . . . . . . . . . . . 191--202 Ludwig Fahrmeir and Thomas Kneib and Susanne Konrath Bayesian regularisation in structured additive regression: a unifying perspective on shrinkage, smoothing and predictor selection . . . . . . . . . . 203--219 Chris Hans Model uncertainty and variable selection in Bayesian lasso regression . . . . . . 221--229 Guillaume Obozinski and Ben Taskar and Michael I. Jordan Joint covariate selection and joint subspace selection for multiple classification problems . . . . . . . . 231--252 Mohamed Hebiri Sparse conformal predictors . . . . . . 253--266 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Evgenia Rubinshtein and Anuj Srivastava Optimal linear projections for enhancing desired data statistics . . . . . . . . 267--282 M. Bevilacqua and J. Mateu and E. Porcu and H. Zhang and A. Zini Weighted composite likelihood-based tests for space-time separability of covariance functions . . . . . . . . . . 283--293 Youngjo Lee and Il Do Ha Orthodox BLUP versus $h$-likelihood methods for inferences about random effects in Tweedie mixed models . . . . 295--303 Mari Myllymäki and Antti Penttinen Bayesian inference for Gaussian excursion set generated Cox processes with set-marking . . . . . . . . . . . . 305--315 Simon Rogers and Mark Girolami and Tamara Polajnar Semi-parametric analysis of multi-rater data . . . . . . . . . . . . . . . . . . 317--334 Merrill W. Liechty and Matthew Tibbits Multivariate sufficient statistics using Kronecker products . . . . . . . . . . . 335--341 Tsung-I Lin Robust mixture modeling using multivariate skew $t$ distributions . . 343--356 M. Sperrin and T. Jaki and E. Wit Probabilistic relabelling strategies for the label switching problem in Bayesian mixture models . . . . . . . . . . . . . 357--366 Javier Roca-Pardiñas and Stefan Sperlich Feasible estimation in generalized structured models . . . . . . . . . . . 367--379 Eun-Kyung Lee and Dianne Cook A projection pursuit index for large $p$ small $n$ data . . . . . . . . . . . . . 381--392 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Marco Sandri and Paola Zuccolotto Analysis and correction of bias in Total Decrease in Node Impurity measures for tree-based algorithms . . . . . . . . . 393--407 Gavino Puggioni and Alan E. Gelfand Analyzing space-time sensor network data under suppression and failure in transmission . . . . . . . . . . . . . . 409--419 Francesco Audrino and Dominik Colangelo Semi-parametric forecasts of the implied volatility surface using regression trees . . . . . . . . . . . . . . . . . 421--434 Farhat Iqbal and Kanchan Mukherjee M-estimators of some GARCH-type models; computation and application . . . . . . 435--445 Kwang Woo Ahn and Kung-Sik Chan Efficient Markov chain Monte Carlo with incomplete multinomial data . . . . . . 447--456 Friedrich Leisch Neighborhood graphs, stripes and shadow plots for cluster visualization . . . . 457--469 Luca Scrucca Dimension reduction for model-based clustering . . . . . . . . . . . . . . . 471--484 David J. Nott and Li Jialiang A sign based loss approach to model selection in nonparametric regression 485--498 I. Gijbels and A. Verhasselt P-splines regression smoothing and difference type of penalty . . . . . . . 499--511 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Christian H. Weiß Rule generation for categorical time series with Markov assumptions . . . . . 1--16 Ivan Kojadinovic and Jun Yan A goodness-of-fit test for multivariate multiparameter copulas based on multiplier central limit theorems . . . 17--30 Frederico Z. Poleto and Julio M. Singer and Carlos Daniel Paulino Missing data mechanisms and their implications on the analysis of categorical data . . . . . . . . . . . . 31--43 Dario Basso and Luigi Salmaso A permutation test for umbrella alternatives . . . . . . . . . . . . . . 45--54 Anne Krampe and Maria Kateri and Sonja Kuhnt Asymmetry models for square contingency tables: exact tests via algebraic statistics . . . . . . . . . . . . . . . 55--67 John W. Lau and Mike K. P. So A Monte Carlo Markov chain algorithm for a class of mixture time series models 69--81 Jin-Chuan Duan and Andras Fulop A stable estimator of the information matrix under EM for dependent data . . . 83--91 Maria Kalli and Jim E. Griffin and Stephen G. Walker Slice sampling mixture models . . . . . 93--105 Edith Gabriel and Denis Allard and Jean-Noël Bacro Estimating and testing zones of abrupt change for spatial data . . . . . . . . 107--120 J.-F. Dupuy and J.-M. Loubes and E. Maza Non parametric estimation of the structural expectation of a stochastic increasing function . . . . . . . . . . 121--136 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Tadayoshi Fushiki Estimation of prediction error by using $K$-fold cross-validation . . . . . . . 137--146 Ronald W. Butler and Robert L. Paige Exact distributional computations for Roy's statistic and the largest eigenvalue of a Wishart distribution . . 147--157 Göran Kauermann and Michael Wegener Functional variance estimation using penalized splines with principal component analysis . . . . . . . . . . . 159--171 Ruggero Bellio and Alessandra R. Brazzale Restricted likelihood inference for generalized linear mixed models . . . . 173--183 Marco Alf\`o and Antonello Maruotti and Giovanni Trovato A finite mixture model for multivariate counts under endogenous selectivity . . 185--202 Katarina Domijan and Simon P. Wilson Bayesian kernel projections for classification of high dimensional data 203--216 Paul Fearnhead and Zhen Liu Efficient Bayesian analysis of multiple changepoint models with dependence across segments . . . . . . . . . . . . 217--229 Helga Wagner Bayesian estimation and stochastic model specification search for dynamic survival models . . . . . . . . . . . . 231--246 Ray-Bing Chen and Chi-Hsiang Chu and Te-You Lai and Ying Nian Wu Stochastic matching pursuit for Bayesian variable selection . . . . . . . . . . . 247--259 Hua Zhou and David Alexander and Kenneth Lange A quasi-Newton acceleration for high-dimensional optimization algorithms 261--273 Nicolas Chopin Fast simulation of truncated Gaussian distributions . . . . . . . . . . . . . 275--288 Christian P. Robert Book Review: James E. Gentle: \booktitleComputational statistics (Statistics and Computing Series) . . . 289--291 Denis Allard Book Review: A. E. Gelfand, P. J. Diggle, M. Fuentes, P. Guttorp (eds.): \booktitleHandbook of spatial statistics 293--294 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Giovanna Menardi Density-based Silhouette diagnostics for clustering methods . . . . . . . . . . . 295--308 Daniel Sabanés Bové and Leonhard Held Bayesian fractional polynomials . . . . 309--324 Li-Mei Zhang and Li-Ping Zhu and Li-Xing Zhu Sufficient dimension reduction in regressions through cumulative Hessian directions . . . . . . . . . . . . . . . 325--334 Ajay Jasra and Christopher C. Holmes Stochastic boosting algorithms . . . . . 335--347 Charles J. Corrado The exact distribution of the maximum, minimum and the range of Multinomial/Dirichlet and Multivariate Hypergeometric frequencies . . . . . . . 349--359 Jeffrey L. Andrews and Paul D. McNicholas Extending mixtures of multivariate $t$-factor analyzers . . . . . . . . . . 361--373 Faming Liang Annealing evolutionary stochastic approximation Monte Carlo for global optimization . . . . . . . . . . . . . . 375--393 Cathy W. S. Chen and Jennifer S. K. Chan and Richard Gerlach and William Y. L. Hsieh A comparison of estimators for regression models with change points . . 395--414 Matthew M. Tibbits and Murali Haran and John C. Liechty Parallel multivariate slice sampling . . 415--430 N. Friel and A. N. Pettitt Classification using distance nearest neighbours . . . . . . . . . . . . . . . 431--437 Loukia Meligkotsidou and Petros Dellaportas Forecasting with non-homogeneous hidden Markov models . . . . . . . . . . . . . 439--449 Samiran Ghosh On the grouped selection and model complexity of the adaptive elastic net 451--462 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Yves F. Atchadé A computational framework for empirical Bayes inference . . . . . . . . . . . . 463--473 Yaming Yu $D$-optimal designs via a cocktail algorithm . . . . . . . . . . . . . . . 475--481 María Xosé Rodríguez-Álvarez and Javier Roca-Pardiñas and Carmen Cadarso-Suárez ROC curve and covariates: extending induced methodology to the non-parametric framework . . . . . . . . 483--499 Chun-Chao Wang and Yi-Ting Hwang A new functional statistic for multivariate normality . . . . . . . . . 501--509 Cinzia Viroli Finite mixtures of matrix normal distributions for classifying three-way data . . . . . . . . . . . . . . . . . . 511--522 Gabriele Soffritti and Giuliano Galimberti Multivariate linear regression with non-normal errors: a solution based on mixture models . . . . . . . . . . . . . 523--536 Julien Chiquet and Yves Grandvalet and Christophe Ambroise Inferring multiple graphical structures 537--553 Yves F. Atchadé and Gareth O. Roberts and Jeffrey S. Rosenthal Towards optimal scaling of Metropolis-coupled Markov chain Monte Carlo . . . . . . . . . . . . . . . . . 555--568 Yi-Ting Hwang and Shih-Kai Chu and Shyh-Tyan Ou Evaluations of FDR-controlling procedures in multiple hypothesis testing . . . . . . . . . . . . . . . . 569--583 L. A. García-Escudero and A. Gordaliza and C. Matrán and A. Mayo-Iscar Exploring the number of groups in robust model-based clustering . . . . . . . . . 585--599 Jun Ma and Sigurbjorg Gudlaugsdottir and Graham Wood Generalized EM estimation for semi-parametric mixture distributions with discretized non-parametric component . . . . . . . . . . . . . . . 601--612 Sylvain Arlot and Alain Celisse Segmentation of the mean of heteroscedastic data via cross-validation . . . . . . . . . . . . 613--632 Luca Martino and Joaquín Míguez A generalization of the adaptive rejection sampling algorithm . . . . . . 633--647 Brendon J. Brewer and Livia B. Pártay and Gábor Csányi Diffusive nested sampling . . . . . . . 649--656 Gregory Gurevich and Albert Vexler A two-sample empirical likelihood ratio test based on samples entropy . . . . . 657--670 Haeran Cho and Piotr Fryzlewicz Multiscale interpretation of taut string estimation and its connection to Unbalanced Haar wavelets . . . . . . . . 671--681 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Zdravko I. Botev and Dirk P. Kroese Efficient Monte Carlo simulation via the generalized splitting method . . . . . . 1--16 Chih-Kang Chu and Jhao-Siang Siao and Lih-Chung Wang and Wen-Shuenn Deng Estimation of 2D jump location curve and 3D jump location surface in nonparametric regression . . . . . . . . 17--31 Kenneth Lo and Raphael Gottardo Flexible mixture modeling via the multivariate $t$ distribution with the Box--Cox transformation: an alternative to the skew-$t$ distribution . . . . . . 33--52 Ian H. Dinwoodie Sequential importance sampling of binary sequences . . . . . . . . . . . . . . . 53--63 Gundula Behrens and Nial Friel and Merrilee Hurn Tuning tempered transitions . . . . . . 65--78 Georgios Papageorgiou and John Hinde Multivariate generalized linear mixed models with semi-nonparametric and smooth nonparametric random effects densities . . . . . . . . . . . . . . . 79--92 Athanasios Kottas and Gilbert W. Fellingham Bayesian semiparametric modeling and inference with mixtures of symmetric distributions . . . . . . . . . . . . . 93--106 Jonathan J. Forster and Roger C. Gill and Antony M. Overstall Reversible jump methods for generalised linear models and generalised linear mixed models . . . . . . . . . . . . . . 107--120 Cristian Meza and Felipe Osorio and Rolando De la Cruz Estimation in nonlinear mixed-effects models using heavy-tailed distributions 121--139 Alessio Farcomeni Quantile regression for longitudinal data based on latent Markov subject-specific parameters . . . . . . 141--152 Martin Slawski The structured elastic net for quantile regression and support vector classification . . . . . . . . . . . . . 153--168 Gianfranco Piras and Nancy Lozano-Gracia Spatial $J$-test: some Monte Carlo evidence . . . . . . . . . . . . . . . . 169--183 Burton Wu and Clare A. McGrory and Anthony N. Pettitt A new variational Bayesian algorithm with application to human mobility pattern modeling . . . . . . . . . . . . 185--203 S. P. Preston and Andrew T. A. Wood Approximation of transition densities of stochastic differential equations by saddlepoint methods applied to small-time Ito--Taylor sample-path expansions . . . . . . . . . . . . . . . 205--217 Nicolas Städler and Peter Bühlmann Missing values: sparse inverse covariance estimation and an extension to sparse regression . . . . . . . . . . 219--235 Giles Hooker and Saharon Rosset Prediction-based regularization using data augmented regression . . . . . . . 237--249 Andrew Redd A comment on the orthogonalization of B-spline basis functions and their derivatives . . . . . . . . . . . . . . 251--257 José R. Berrendero and Antonio Cuevas and Beatriz Pateiro-López A multivariate uniformity test for the case of unknown support . . . . . . . . 259--271 Jianhui Ning and Philip E. Cheng A comparison study of nonparametric imputation methods . . . . . . . . . . . 273--285 Hsiu J. Ho and Saumyadipta Pyne and Tsung I. Lin Maximum likelihood inference for mixtures of skew Student-$t$-normal distributions through practical EM-type algorithms . . . . . . . . . . . . . . . 287--299 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Weixin Yao Model based labeling for mixture models 337--347 Guglielmo Maria Caporale and Juncal Cunado and Luis A. Gil-Alana Deterministic versus stochastic seasonal fractional integration and structural breaks . . . . . . . . . . . . . . . . . 349--358 D. Lamnisos and J. E. Griffin and M. F. J. Steel Cross-validation prior choice in Bayesian probit regression with many covariates . . . . . . . . . . . . . . . 359--373 Ata Kabán Non-parametric detection of meaningless distances in high dimensional data . . . 375--385 T. J. Harris and W. Yu Variance decompositions of nonlinear time series using stochastic simulation and sensitivity analysis . . . . . . . . 387--396 Jian Chen and Jeffrey S. Rosenthal Decrypting classical cipher text using Markov chain Monte Carlo . . . . . . . . 397--413 Jason Wyse and Nial Friel Block clustering with collapsed latent block models . . . . . . . . . . . . . . 415--428 David Campbell and Russell J. Steele Smooth functional tempering for nonlinear differential equation models 429--443 Nickolay T. Trendafilov DINDSCAL: direct INDSCAL . . . . . . . . 445--454 Jean-Patrick Baudry and Cathy Maugis and Bertrand Michel Slope heuristics: overview and implementation . . . . . . . . . . . . . 455--470 Kris Boudt and Jonathan Cornelissen and Christophe Croux The Gaussian rank correlation estimator: robustness properties . . . . . . . . . 471--483 A. Lung-Yut-Fong and C. Lévy-Leduc and O. Cappé Distributed detection/localization of change-points in high-dimensional network traffic data . . . . . . . . . . 485--496 David J. Nott and Minh-Ngoc Tran and Chenlei Leng Variational approximation for heteroscedastic linear models and matching pursuit algorithms . . . . . . 497--512 Michael Amrein and Hans R. Künsch Rate estimation in partially observed Markov jump processes with measurement errors . . . . . . . . . . . . . . . . . 513--526 Hirokazu Yanagihara A non-iterative optimization method for smoothness in penalized spline regression . . . . . . . . . . . . . . . 527--544 Gerhard Tutz and Sebastian Petry Nonparametric estimation of the link function including variable selection 545--561 Achilleas Achilleos and Aurore Delaigle Local bandwidth selectors for deconvolution kernel density estimation 563--577 François Caron and Arnaud Doucet and Raphael Gottardo On-line changepoint detection and parameter estimation with application to genomic data . . . . . . . . . . . . . . 579--595 Hossein Baghishani and Håvard Rue and Mohsen Mohammadzadeh On a hybrid data cloning method and its application in generalized linear mixed models . . . . . . . . . . . . . . . . . 597--613 Erik Lindström A regularized bridge sampler for sparsely sampled diffusions . . . . . . 615--623 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Anestis Antoniadis and Alberto Pasanisi Modeling of computer experiments for uncertainty propagation and sensitivity analysis . . . . . . . . . . . . . . . . 677--679 Luc Pronzato and Werner G. Müller Design of computer experiments: space filling and beyond . . . . . . . . . . . 681--701 Yves Auffray and Pierre Barbillon and Jean-Michel Marin Maximin design on non hypercube domains and kernel interpolation . . . . . . . . 703--712 Robert B. Gramacy and Herbert K. H. Lee Cases for the nugget in modeling computer experiments . . . . . . . . . . 713--722 Thomas Muehlenstaedt and Olivier Roustant and Laurent Carraro and Sonja Kuhnt Data-driven Kriging models based on FANOVA-decomposition . . . . . . . . . . 723--738 Valeria Sambucini Confidence regions for the stationary point of a quadratic response surface based on the asymptotic distribution of its MLE . . . . . . . . . . . . . . . . 739--751 Serge Cohen and Sébastien Déjean and Sébastien Gadat Adaptive sequential design for regression on multi-resolution bases . . 753--772 Julien Bect and David Ginsbourger and Ling Li and Victor Picheny and Emmanuel Vazquez Sequential design of computer experiments for the estimation of a probability of failure . . . . . . . . . 773--793 F. Cérou and P. Del Moral and T. Furon and A. Guyader Sequential Monte Carlo for rare event estimation . . . . . . . . . . . . . . . 795--808 Miguel Munoz Zuniga and Josselin Garnier and Emmanuel Remy and Etienne de Rocquigny Analysis of adaptive directional stratification for the controlled estimation of rare event probabilities 809--821 Astrid Jourdan Global sensitivity analysis using complex linear models . . . . . . . . . 823--831 Amandine Marrel and Bertrand Iooss and Sébastien Da Veiga and Mathieu Ribatet Global sensitivity analysis of stochastic computer models with joint metamodels . . . . . . . . . . . . . . . 833--847 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Petros Dellaportas and Mohsen Pourahmadi Cholesky-GARCH models with applications to finance . . . . . . . . . . . . . . . 849--855 Jiguo Cao Estimating generalized semiparametric additive models using parameter cascading . . . . . . . . . . . . . . . 857--865 Joseph Sexton and Petter Laake Boosted coefficient models . . . . . . . 867--876 Marina I. Knight and Matthew A. Nunes and Guy P. Nason Spectral estimation for locally stationary time series with missing observations . . . . . . . . . . . . . . 877--895 Nicolas Chopin and Tony Leli\`evre and Gabriel Stoltz Free energy methods for Bayesian inference: efficient exploration of univariate Gaussian mixture posteriors 897--916 G. Rigaill and E. Lebarbier and S. Robin Exact posterior distributions and model selection criteria for multiple change-point detection problems . . . . 917--929 Tomás Mrkvicka and Samuel Soubeyrand and Joël Chadoeuf Goodness-of-fit test of the mark distribution in a point process with non-stationary marks . . . . . . . . . . 931--943 Ulrich Paquet and Blaise Thomson and Ole Winther A hierarchical model for ordinal matrix factorization . . . . . . . . . . . . . 945--957 Woojoo Lee and Youngjo Lee Modifications of REML algorithm for HGLMs . . . . . . . . . . . . . . . . . 959--966 Simos G. Meintanis and Jochen Einbeck Goodness-of-fit tests in semi-linear models . . . . . . . . . . . . . . . . . 967--979 J. A. D. Aston and J. Y. Peng and D. E. K. Martin Implied distributions in multiple change point problems . . . . . . . . . . . . . 981--993 Steven G. Gilmour John Lawson: Design and analysis of experiments with SAS . . . . . . . . . . 995--996 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Matti Vihola Robust adaptive Metropolis algorithm with coerced acceptance rate . . . . . . 997--1008 Pierre Del Moral and Arnaud Doucet and Ajay Jasra An adaptive sequential Monte Carlo method for approximate Bayesian computation . . . . . . . . . . . . . . 1009--1020 Jeffrey L. Andrews and Paul D. McNicholas Model-based clustering, classification, and discriminant analysis via mixtures of multivariate $t$-distributions . . . 1021--1029 Joshua C. C. Chan and Dirk P. Kroese Improved cross-entropy method for estimation . . . . . . . . . . . . . . . 1031--1040 Tristan Marshall and Gareth Roberts An adaptive approach to Langevin MCMC 1041--1057 Jiguo Cao and Jing Cai and Liangliang Wang Estimating curves and derivatives with parametric penalized spline smoothing 1059--1067 Minh-Ngoc Tran and David J. Nott and Chenlei Leng The predictive Lasso . . . . . . . . . . 1069--1084 Xin-Yuan Song and Zhao-Hua Lu Semiparametric transformation models with Bayesian $P$-splines . . . . . . . 1085--1098 Gert van Valkenhoef and Tommi Tervonen and Bert de Brock and Hans Hillege Algorithmic parameterization of mixed treatment comparisons . . . . . . . . . 1099--1111 Sophie Donnet and Jean-Michel Marin An empirical Bayes procedure for the selection of Gaussian graphical models 1113--1123 Ping-Feng Xu and Jianhua Guo and Man-Lai Tang An improved Hara--Takamura procedure by sharing computations on junction tree in Gaussian graphical models . . . . . . . 1125--1133 Wai-Yin Poon and Hai-Bin Wang Latent variable models with ordinal categorical covariates . . . . . . . . . 1135--1154 Leonid (Aryeh) Kontorovich Statistical estimation with bounded memory . . . . . . . . . . . . . . . . . 1155--1164 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Gilles Celeux Approximate Bayesian computation methods 1165--1166 Jean-Michel Marin and Pierre Pudlo and Christian P. Robert and Robin J. Ryder Approximate Bayesian computational methods . . . . . . . . . . . . . . . . 1167--1180 Chris P. Barnes and Sarah Filippi and Michael P. H. Stumpf and Thomas Thorne Considerate approaches to constructing summary statistics for ABC model selection . . . . . . . . . . . . . . . 1181--1197 R. McVinish Improving ABC for quantile distributions 1199--1207 G. W. Peters and Y. Fan and S. A. Sisson On sequential Monte Carlo, partial rejection control and approximate Bayesian computation . . . . . . . . . . 1209--1222 Ajay Jasra and Sumeetpal S. Singh and James S. Martin and Emma McCoy Filtering via approximate Bayesian computation . . . . . . . . . . . . . . 1223--1237 Peter Neal Efficient likelihood-free Bayesian Computation for household epidemics . . 1239--1256 Andrea Rau and Florence Jaffrézic and Jean-Louis Foulley and R. W. Doerge Reverse engineering gene regulatory networks using approximate Bayesian computation . . . . . . . . . . . . . . 1257--1271 David J. Nott and Lucy Marshall and Tran Minh Ngoc The ensemble Kalman filter is an ABC algorithm . . . . . . . . . . . . . . . 1273--1276 Anonymous Help & Contacts . . . . . . . . . . . . . ??
M. Kolossiatis and J. E. Griffin and M. F. J. Steel On Bayesian nonparametric modelling of two correlated distributions . . . . . . 1--15 Mehdi Maadooliat and Mohsen Pourahmadi and Jianhua Z. Huang Robust estimation of the correlation matrix of longitudinal data . . . . . . 17--28 Nathalie Peyrard and Régis Sabbadin and Daniel Spring and Barry Brook and Ralph MacNally Model-based adaptive spatial sampling for occurrence map construction . . . . 29--42 Raquel Prado and Hedibert F. Lopes Sequential parameter learning and filtering in structured autoregressive state-space models . . . . . . . . . . . 43--57 Jukka Corander and Yaqiong Cui and Timo Koski and Jukka Sirén Have I seen you before? Principles of Bayesian predictive classification revisited . . . . . . . . . . . . . . . 59--73 Philippe Lambert Nonparametric additive location-scale models for interval censored data . . . 75--90 Joaquín Míguez and Dan Crisan and Petar M. Djuri\'c On the convergence of two sequential Monte Carlo methods for maximum a posteriori sequence estimation and stochastic global optimization . . . . . 91--107 Joris Mulder and Jean-Paul Fox Bayesian tests on components of the compound symmetry covariance matrix . . 109--122 Jim E. Griffin and Stephen G. Walker On adaptive Metropolis--Hastings methods 123--134 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Fabian Sobotka and Göran Kauermann and Linda Schulze Waltrup and Thomas Kneib On confidence intervals for semiparametric expectile regression . . 135--148 Ping-Hung Hsieh A nonparametric assessment of model adequacy based on Kullback--Leibler divergence . . . . . . . . . . . . . . . 149--162 Christian Schäfer and Nicolas Chopin Sequential Monte Carlo on large binary sampling spaces . . . . . . . . . . . . 163--184 Roberto Casarin and Radu Craiu and Fabrizio Leisen Interacting multiple try algorithms with different proposal distributions . . . . 185--200 Jin-Hong Park Multiple-index approach to multiple autoregressive time series model . . . . 201--208 Nickolay T. Trendafilov and Steffen Unkel and Wojtek Krzanowski Exploratory factor and principal component analyses: some new aspects . . 209--220 Baisuo Jin and Xiaoping Shi and Yuehua Wu A novel and fast methodology for simultaneous multiple structural break estimation and variable selection for nonstationary time series models . . . . 221--231 Chew-Seng Chee and Yong Wang Estimation of finite mixtures with symmetric components . . . . . . . . . . 233--249 Carsten Botts and Wolfgang Hörmann and Josef Leydold Transformed density rejection with inflection points . . . . . . . . . . . 251--260 Siddhartha Chib and Edward Greenberg On conditional variance estimation in nonparametric regression . . . . . . . . 261--270 Zdravko I. Botev and Pierre L'Ecuyer and Bruno Tuffin Markov chain importance sampling with applications to rare event probability estimation . . . . . . . . . . . . . . . 271--285 Peter Milner and Colin S. Gillespie and Darren J. Wilkinson Moment closure based parameter inference of stochastic kinetic models . . . . . . 287--295 Anonymous Help & Contacts . . . . . . . . . . . . . ??
A. Bar-Hen and J. Chadoeuf and H. Dessard and P. Monestiez Estimating second order characteristics of point processes with known independent noise . . . . . . . . . . . 297--309 Joyee Ghosh and Jerome P. Reiter Secure Bayesian model averaging for horizontally partitioned data . . . . . 311--322 Me\"\ili Baragatti and Agn\`es Grimaud and Denys Pommeret Parallel tempering with equi-energy moves . . . . . . . . . . . . . . . . . 323--339 Simon N. Wood and Fabian Scheipl and Julian J. Faraway Straightforward intermediate rank tensor product smoothing in mixed models . . . 341--360 Anastasia Lykou and Ioannis Ntzoufras On Bayesian lasso variable selection and the specification of the shrinkage parameter . . . . . . . . . . . . . . . 361--390 Douglas P. Wiens Designs for weighted least squares regression, with estimated weights . . . 391--401 Cristian Gatu and Erricos John Kontoghiorghes A fast algorithm for non-negativity model selection . . . . . . . . . . . . 403--411 Estelle Kuhn and Charles El-Nouty On a convergent stochastic estimation algorithm for frailty models . . . . . . 413--423 Eduardo L. Montoya and Wendy Meiring On the relative efficiency of a monotone parameter curve estimator in a functional nonlinear model . . . . . . . 425--436 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Yuao Hu and Robert B. Gramacy and Heng Lian Bayesian quantile regression for single-index models . . . . . . . . . . 437--454 Zhensheng Huang and Riquan Zhang Profile empirical-likelihood inferences for the single-index-coefficient regression model . . . . . . . . . . . . 455--465 Matthew Fitzpatrick and Dobrin Marchev Efficient Bayesian estimation of the multivariate Double Chain Markov Model 467--480 Man-Suk Oh Bayesian multiple comparison of models for binary data with inequality constraints . . . . . . . . . . . . . . 481--490 D. Fouskakis and I. Ntzoufras Computation for intrinsic variable selection in normal regression models via expected-posterior prior . . . . . . 491--499 Erlend Aune and Jo Eidsvik and Yvo Pokern Iterative numerical methods for sampling from high dimensional Gaussian distributions . . . . . . . . . . . . . 501--521 Jean-Pierre Gauchi and Jean-Pierre Vila Nonparametric particle filtering approaches for identification and inference in nonlinear state-space dynamic systems . . . . . . . . . . . . 523--533 Me\"\ili Baragatti and Agn\`es Grimaud and Denys Pommeret Likelihood-free parallel tempering . . . 535--549 Marco Riani and Anthony C. Atkinson and Giulio Fanti and Fabio Crosilla Regression analysis with partially labelled regressors: carbon dating of the Shroud of Turin . . . . . . . . . . 551--561 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Wei-Ting Yao and Han-Ming Wu Isometric sliced inverse regression for nonlinear manifold learning . . . . . . 563--576 George Iliopoulos and Sonia Malefaki Variance reduction of estimators arising from Metropolis--Hastings algorithms . . 577--587 Liugen Xue and Zhen Pang Statistical inference for a single-index varying-coefficient model . . . . . . . 589--599 Matthias Chung and Qi Long and Brent A. Johnson A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems . . . . . . . . 601--614 R. Lebrun Efficient time/space algorithm to compute rectangular probabilities of multinomial, multivariate hypergeometric and multivariate Pólya distributions . . 615--623 Giuliano Galimberti and Gabriele Soffritti Using conditional independence for parsimonious model-based Gaussian clustering . . . . . . . . . . . . . . . 625--638 Abouzar Bazyari and Fortunato Pesarin Parametric and permutation testing for multivariate monotonic alternatives . . 639--652 Antonietta Mira and Reza Solgi and Daniele Imparato Zero variance Markov chain Monte Carlo for Bayesian estimators . . . . . . . . 653--662 Ray-Bing Chen and Dai-Ni Hsieh and Ying Hung and Weichung Wang Optimizing Latin hypercube designs by particle swarm . . . . . . . . . . . . . 663--676 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Steffen Liebscher and Thomas Kirschstein and Claudia Becker RDELA --- a Delaunay-triangulation-based, location and covariance estimator with high breakdown point . . . . . . . . . . . . 677--688 A. H. Welsh and Douglas P. Wiens Robust model-based sampling designs . . 689--701 Alicja Jokiel-Rokita and Michal Pulit Nonparametric estimation of the ROC curve based on smoothed empirical distribution functions . . . . . . . . . 703--712 Yong Wang and Stephen M. Taylor Efficient computation of nonparametric survival functions via a hierarchical mixture formulation . . . . . . . . . . 713--725 Miguel González and Cristina Gutiérrez and Rodrigo Martínez Parametric Bayesian inference for $Y$-linked two-sex branching models . . 727--741 Yanwei Zhang Likelihood-based and Bayesian methods for Tweedie compound Poisson linear mixed models . . . . . . . . . . . . . . 743--757 Yohan Petetin and François Desbouvries Optimal SIR algorithm vs. fully adapted auxiliary particle filter: a non asymptotic analysis . . . . . . . . . . 759--775 P.-A. Cornillon and N. Hengartner and N. Jegou and E. Matzner-Lòber Iterative bias reduction: a comparative study . . . . . . . . . . . . . . . . . 777--791 Yoshihiro Hirose and Fumiyasu Komaki Edge selection based on the geometry of dually flat spaces for Gaussian graphical models . . . . . . . . . . . . 793--800 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Ajay Jasra and Nikolas Kantas and Adam Persing Bayesian parameter inference for partially observed stopped processes . . 1--20 Alexander Hapfelmeier and Torsten Hothorn and Kurt Ulm and Carolin Strobl A new variable importance measure for random forests with missing data . . . . 21--34 Carlos E. Rodríguez and Stephen G. Walker Univariate Bayesian nonparametric mixture modeling with unimodal kernels 35--49 Xiaohui Liu and Yijun Zuo Computing projection depth and its associated estimators . . . . . . . . . 51--63 A. Martín Andrés and M. Álvarez Hernández Two-tailed approximate confidence intervals for the ratio of proportions 65--75 Gabriele Fiorentini and Christophe Planas and Alessandro Rossi Efficient MCMC sampling in dynamic mixture models . . . . . . . . . . . . . 77--89 T. Mrkvicka and M. Muska and J. Kubecka Two step estimation for Neyman--Scott point process with inhomogeneous cluster centers . . . . . . . . . . . . . . . . 91--100 Linda M. Haines and Allan E. Clark The construction of optimal designs for dose-escalation studies . . . . . . . . 101--109 L. Wang and J. Cao and J. O. Ramsay and D. M. Burger and C. J. L. Laporte and J. K. Rockstroh Estimating mixed-effects differential equation models . . . . . . . . . . . . 111--121 Chenlei Leng and Weiping Zhang Smoothing combined estimating equations in quantile regression for longitudinal data . . . . . . . . . . . . . . . . . . 123--136 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Andreas Groll and Gerhard Tutz Variable selection for generalized linear mixed models by $ L_1 $-penalized estimation . . . . . . . . . . . . . . . 137--154 Andrew C. Titman Estimating parametric semi-Markov models from panel data using phase-type approximations . . . . . . . . . . . . . 155--164 J. L. Scealy and A. H. Welsh Fitting Kent models to compositional data with small concentration . . . . . 165--179 Sharon Lee and Geoffrey J. McLachlan Finite mixtures of multivariate skew $t$-distributions: some recent and new results . . . . . . . . . . . . . . . . 181--202 Ryan P. Browne and Paul D. McNicholas Orthogonal Stiefel manifold optimization for eigen-decomposed covariance parameter estimation in mixture models 203--210 Dexter O. Cahoy and Federico Polito Parameter estimation for fractional birth and fractional death processes . . 211--222 Stefan Lang and Nikolaus Umlauf and Peter Wechselberger and Kenneth Harttgen and Thomas Kneib Multilevel structured additive regression . . . . . . . . . . . . . . . 223--238 Luc Devroye Random variate generation for the generalized inverse Gaussian distribution . . . . . . . . . . . . . . 239--246 Erlend Aune and Daniel P. Simpson and Jo Eidsvik Parameter estimation in high dimensional Gaussian distributions . . . . . . . . . 247--263 Derek S. Young Mixtures of regressions with changepoints . . . . . . . . . . . . . . 265--281 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Frank Konietschke and Markus Pauly Bootstrapping and permuting paired $t$-test type statistics . . . . . . . . 283--296 Loukia Meligkotsidou and Elias Tzavalis and Ioannis D. Vrontos A Bayesian method of distinguishing unit root from stationary processes based on panel data models with cross-sectional dependence . . . . . . . . . . . . . . . 297--315 Julien Cornebise and Eric Moulines and Jimmy Olsson Adaptive sequential Monte Carlo by means of mixture of experts . . . . . . . . . 317--337 Babak Shahbaba and Shiwei Lan and Wesley O. Johnson and Radford M. Neal Split Hamiltonian Monte Carlo . . . . . 339--349 Davide Ferrari and Matteo Borrotti and Davide De March Response improvement in complex experiments by co-information composite likelihood optimization . . . . . . . . 351--363 Oguz Akbilgic and Hamparsum Bozdogan and M. Erdal Balaban A novel Hybrid RBF Neural Networks model as a forecaster . . . . . . . . . . . . 365--375 Lorenzo Hernández and Jorge Tejero and Alberto Su and Santiago Carrillo-Menéndez Percentiles of sums of heavy-tailed random variables: beyond the single-loss approximation . . . . . . . . . . . . . 377--397 Yi-Ting Hwang and Hsun-Chih Kuo and Chun-Chao Wang and Meng Feng Lee Estimating the number of true null hypotheses in multiple hypothesis testing . . . . . . . . . . . . . . . . 399--416 Sara Viviani and Marco Alfó and Dimitris Rizopoulos Generalized linear mixed joint model for longitudinal and survival outcomes . . . 417--427 Seokho Lee and Jianhua Z. Huang A biclustering algorithm for binary matrices based on penalized Bernoulli likelihood . . . . . . . . . . . . . . . 429--441 Ana Arribas-Gil and Karine Bertin and Cristian Meza and Vincent Rivoirard LASSO-type estimators for semiparametric nonlinear mixed-effects models estimation . . . . . . . . . . . . . . . 443--460 Marco Geraci and Matteo Bottai Linear quantile mixed models . . . . . . 461--479 Sonja Kuhnt and Fabio Rapallo and André Rehage Outlier detection in contingency tables based on minimal patterns . . . . . . . 481--491 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Stevenn Volant and Caroline Bérard and Marie-Laure Martin-Magniette and Stéphane Robin Hidden Markov Models with mixtures as emission distributions . . . . . . . . . 493--504 Sooyoung Cheon and Faming Liang and Yuguo Chen and Kai Yu Stochastic approximation Monte Carlo importance sampling for approximating exact conditional probabilities . . . . 505--520 Hao Wang Coordinate descent algorithm for covariance graphical lasso . . . . . . . 521--529 Tsung-I Lin and Hsiu J. Ho and Chia-Rong Lee Flexible mixture modelling using the multivariate skew-$t$-normal distribution . . . . . . . . . . . . . . 531--546 Wolfgang Hörmann and Josef Leydold Generating generalized inverse Gaussian random variates . . . . . . . . . . . . 547--557 Sy Han Chiou and Sangwook Kang and Jun Yan Fast accelerated failure time modeling for case-cohort data . . . . . . . . . . 559--568 Isabella Gollini and Thomas Brendan Murphy Mixture of latent trait analyzers for model-based clustering of categorical data . . . . . . . . . . . . . . . . . . 569--588 Lucio Barabesi and Luca Pratelli A note on a universal random variate generator for integer-valued random variables . . . . . . . . . . . . . . . 589--596 Matthias Borowski and Roland Fried Online signal extraction by robust regression in moving windows with data-adaptive width selection . . . . . 597--613 Claudia Fassino and Giovanni Pistone and Eva Riccomagno The algebra of interpolatory cubature formulæ for generic nodes . . . . . . . . 615--632 Jürgen Franz and Alicja Jokiel-Rokita and Ryszard Magiera Prediction in trend-renewal processes for repairable systems . . . . . . . . . 633--649 Jean-Noel Bacro and Carlo Gaetan Estimation of spatial max-stable models using threshold exceedances . . . . . . 651--662 Chris J. Lloyd and Degui Li Computing highly accurate confidence limits from discrete data using importance sampling . . . . . . . . . . 663--673 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Jean-Benoist Leger and Corinne Vacher and Jean-Jacques Daudin Detection of structurally homogeneous subsets in graphs . . . . . . . . . . . 675--692 Marc Lavielle and Cyprien Mbogning An improved SAEM algorithm for maximum likelihood estimation in mixtures of non linear mixed effects models . . . . . . 693--707 Nial Friel and Merrilee Hurn and Jason Wyse Improving power posterior estimation of statistical evidence . . . . . . . . . . 709--723 Jianxin Pan and Chao Huang Random effects selection in generalized linear mixed models via shrinkage penalty function . . . . . . . . . . . . 725--738 Theodoros Economou and Trevor C. Bailey and Zoran Kapelan MCMC implementation for Bayesian hidden semi-Markov models with illustrative applications . . . . . . . . . . . . . . 739--752 Giovanna Menardi and Adelchi Azzalini An advancement in clustering via nonparametric density estimation . . . . 753--767 Alan Ricardo da Silva and Thais Carvalho Valadares Rodrigues Geographically Weighted Negative Binomial Regression-incorporating overdispersion . . . . . . . . . . . . . 769--783 Geir Drage Berentsen and Dag Tjòstheim Recognizing and visualizing departures from independence in bivariate data using local Gaussian correlation . . . . 785--801 Yi Yu and Yang Feng APPLE: approximate path for penalized likelihood estimators . . . . . . . . . 803--819 I. N. M. Shaharanee and F. Hadzic Evaluation and optimization of frequent, closed and maximal association rule based classification . . . . . . . . . . 821--843 Shih-Chang Lee and Ning-Ning Pang and Wen-Jer Tzeng Resolution dependence of the maximal information coefficient for noiseless relationship . . . . . . . . . . . . . . 845--852 Limin Peng and Jinfeng Xu and Nancy Kutner Shrinkage estimation of varying covariate effects based on quantile regression . . . . . . . . . . . . . . . 853--869 Dingfeng Jiang and Jian Huang Majorization minimization by coordinate descent for concave penalized generalized linear models . . . . . . . 871--883 Yonggang Yao and Yoonkyung Lee Another look at linear programming for feature selection via methods of regularization . . . . . . . . . . . . . 885--905 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Alessio Farcomeni Snipping for robust $k$-means clustering under component-wise contamination . . . 907--919 Ian C. Marschner Combinatorial EM algorithms . . . . . . 921--940 Livio Finos and Dario Basso Permutation tests for between-unit fixed effects in multivariate generalized linear mixed models . . . . . . . . . . 941--952 Christophe Biernacki and Alexandre Lourme Stable and visualizable Gaussian parsimonious clustering models . . . . . 953--969 Florence Forbes and Darren Wraith A new family of multivariate heavy-tailed distributions with variable marginal amounts of tailweight: application to robust clustering . . . . 971--984 Jianbo Li and Zhensheng Huang and Heng Lian Empirical likelihood inference for general transformation models with right censored data . . . . . . . . . . . . . 985--995 Andrew Gelman and Jessica Hwang and Aki Vehtari Understanding predictive information criteria for Bayesian models . . . . . . 997--1016 Gordon J. Ross Sequential change detection in the presence of unknown parameters . . . . . 1017--1030 Elizabeth Ann Maharaj Classification of cyclical time series using complex demodulation . . . . . . . 1031--1046 Junjing Lin and Michael Ludkovski Sequential Bayesian inference in hidden Markov stochastic kinetic models with application to detection and response to seasonal epidemics . . . . . . . . . . . 1047--1062 Belmiro P. M. Duarte and Weng Kee Wong A semi-infinite programming based algorithm for finding minimax optimal designs for nonlinear models . . . . . . 1063--1080 Göran Kauermann and Christian Schellhase Flexible pair-copula estimation in $D$-vines using bivariate penalized splines . . . . . . . . . . . . . . . . 1081--1100 Hongxia Yang and Fei Liu and Chunlin Ji and David Dunson Adaptive sampling for Bayesian geospatial models . . . . . . . . . . . 1101--1110 Marcos O. Prates and Denise R. Costa and Victor H. Lachos Generalized linear mixed models for correlated binary data with $t$-link . . 1111--1123 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Antonietta Mira and Christian P. Robert An introduction to the special issue ``Joint IMS--ISBA meeting --- MCMSki 4'' 1--1 Heikki Haario Introduction to ``Quantitative bounds of convergence for geometrically ergodic Markov Chain in the Wasserstein distance with application to the Metropolis adjusted Langevin algorithm'' by A. Durmus, É. Moulines . . . . . . . . . . . 3--3 Alain Durmus and Éric Moulines Quantitative bounds of convergence for geometrically ergodic Markov chain in the Wasserstein distance with application to the Metropolis Adjusted Langevin Algorithm . . . . . . . . . . . 5--19 Nial Friel Introduction to ``Pre-processing for approximate Bayesian computation in image analysis'' by M. Moores, C. Drovandi, K. Mengersen, C. Robert . . . 21--21 Matthew T. Moores and Christopher C. Drovandi and Kerrie Mengersen and Christian P. Robert Pre-processing for approximate Bayesian computation in image analysis . . . . . 23--33 Bradley Carlin Introduction to ``Cuts in Bayesian graphical models'' by M. Plummer . . . . 35--35 Martyn Plummer Cuts in Bayesian graphical models . . . 37--43 Håvard Rue Introduction to ``Fast matrix computations for functional additive models'' by S. Barthelmé . . . . . . . . 45--45 Simon Barthelmé Fast matrix computations for functional additive models . . . . . . . . . . . . 47--63 Peter Mueller Introduction to ``On a class of $ \sigma $-stable Poisson--Kingman models and an effective marginalized sampler'' by S. Favaro, M. Lomeli, Y. W. Teh . . . . . . 65--66 S. Favaro and M. Lomeli and Y. W. Teh On a class of $ \sigma $-stable Poisson--Kingman models and an effective marginalized sampler . . . . . . . . . . 67--78 Christophe Andrieu Introduction to ``Particle Metropolis--Hastings using gradient and Hessian information'' by J. Dahlin, F. Lindsten, T. Schön . . . . . . . . . . . 79--79 Johan Dahlin and Fredrik Lindsten and Thomas B. Schön Particle Metropolis--Hastings using gradient and Hessian information . . . . 81--92 Stefano Peluso Introduction to ``On the use of Markov chain Monte Carlo methods for the sampling of mixture models'' by R. Douc, F. Maire, J. Olsson . . . . . . . . . . 93--94 Randal Douc and Florian Maire and Jimmy Olsson On the use of Markov chain Monte Carlo methods for the sampling of mixture models: a statistical perspective . . . 95--110 Nial Friel Introduction to ``Efficient computational strategies for doubly intractable problems with applications to Bayesian social networks'' by A. Caimo, A. Mira . . . . . . . . . . . . . 111--111 Alberto Caimo and Antonietta Mira Efficient computational strategies for doubly intractable problems with applications to Bayesian social networks 113--125 Christian P. Robert Introduction to ``Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields'' by J. Stoehr, P. Pudlo, L. Cucala . . . . . . 127--127 Julien Stoehr and Pierre Pudlo and Lionel Cucala Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields . . . . . . . . . . . . . 129--141 Robin J. Ryder Introduction to ``Scalable inference for Markov processes with intractable likelihoods'' by J. Owen, D. Wilkinson, C. Gillespie . . . . . . . . . . . . . . 143--143 Jamie Owen and Darren J. Wilkinson and Colin S. Gillespie Scalable inference for Markov processes with intractable likelihoods . . . . . . 145--156 Colin Fox Introduction to ``Efficient local updates for undirected graphical models'' by F. Stingo, G. Marchetti . . 157--157 Francesco Stingo and Giovanni M. Marchetti Efficient local updates for undirected graphical models . . . . . . . . . . . . 159--171
Patrick Breheny and Jian Huang Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors . . . . . 173--187 Mengmeng Guo and Lan Zhou and Jianhua Z. Huang and Wolfgang Karl Härdle Functional data analysis of generalized regression quantiles . . . . . . . . . . 189--202 Livio Corain and Luigi Salmaso Improving power of multivariate combination-based permutation tests . . 203--214 Francesca Greselin and Salvatore Ingrassia Maximum likelihood estimation in constrained parameter spaces for mixtures of factor analyzers . . . . . . 215--226 Jack Kuipers and Giusi Moffa Uniform random generation of large acyclic digraphs . . . . . . . . . . . . 227--242 Christelle Vergé and Cyrille Dubarry and Pierre Del Moral and Eric Moulines On parallel implementation of sequential Monte Carlo methods: the island particle model . . . . . . . . . . . . . . . . . 243--260 Francesca Martella and Donatella Vicari and Maurizio Vichi Partitioning predictors in multivariate regression models . . . . . . . . . . . 261--272 Ray-Bing Chen and Meihui Guo and Wolfgang K. Härdle and Shih-Feng Huang COPICA-independent component analysis via copula techniques . . . . . . . . . 273--288 S. R. White and T. Kypraios and S. P. Preston Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution . . 289--301 Yann Guédon Segmentation uncertainty in multiple change-point models . . . . . . . . . . 303--320 Tomonari Sei and Alfred Kume Calculating the normalising constant of the Bingham distribution on the sphere using the holonomic gradient method . . 321--332 Peter Neal and Theodore Kypraios Exact Bayesian inference via data augmentation . . . . . . . . . . . . . . 333--347 Xuxu Wang and Yong Wang Nonparametric multivariate density estimation using mixtures . . . . . . . 349--364 Roland Fried and Inoncent Agueusop and Björn Bornkamp and Konstantinos Fokianos and Jana Fruth and Katja Ickstadt Retrospective Bayesian outlier detection in INGARCH series . . . . . . . . . . . 365--374 Helgi Tómasson Some computational aspects of Gaussian CARMA modelling . . . . . . . . . . . . 375--387 Avishek Chakraborty and Swarup De and Kenneth P. Bowman and Huiyan Sang and Marc G. Genton and Bani K. Mallick An adaptive spatial model for precipitation data from multiple satellites over large regions . . . . . 389--405 Eugenia Koblents and Joaquín Míguez A population Monte Carlo scheme with transformed weights and its application to stochastic kinetic models . . . . . . 407--425 Simo Särkkä and Jouni Hartikainen and Isambi Sailon Mbalawata and Heikki Haario Posterior inference on parameters of stochastic differential equations via non-linear Gaussian filtering and adaptive MCMC . . . . . . . . . . . . . 427--437 Ricardo A. Maronna and Fernanda Méndez and Víctor J. Yohai Robust nonlinear principal components 439--448 Laure Sansonnet and Christine Tuleau-Malot A model of Poissonian interactions and detection of dependence . . . . . . . . 449--470
L. Naranjo and C. J. Pérez and J. Martín Bayesian analysis of some models that use the asymmetric exponential power distribution . . . . . . . . . . . . . . 497--514 Francesco Bartolucci and Alessio Farcomeni Information matrix for hidden Markov models with covariates . . . . . . . . . 515--526 Therese Graversen and Steffen Lauritzen Computational aspects of DNA mixture analysis . . . . . . . . . . . . . . . . 527--541 Natalya Pya and Simon N. Wood Shape constrained additive models . . . 543--559 Elias D. Nino Ruiz and Adrian Sandu and Jeffrey Anderson An efficient implementation of the ensemble Kalman filter based on an iterative Sherman--Morrison formula . . 561--577 Gaorong Li and Peng Lai and Heng Lian Variable selection and estimation for partially linear single-index models with longitudinal data . . . . . . . . . 579--593 Sinan Yildirim and Lan Jiang and Sumeetpal S. Singh and Thomas A. Dean Calibrating the Gaussian multi-target tracking model . . . . . . . . . . . . . 595--608 Niels Richard Hansen Nonparametric likelihood based estimation of linear filters for point processes . . . . . . . . . . . . . . . 609--618 L. A. García-Escudero and A. Gordaliza and C. Matrán and A. Mayo-Iscar Avoiding spurious local maximizers in mixture modeling . . . . . . . . . . . . 619--633 Steve Su Flexible parametric quantile regression model . . . . . . . . . . . . . . . . . 635--650 Yuao Hu and Kaifeng Zhao and Heng Lian Bayesian quantile regression for partially linear additive models . . . . 651--668 Alexei Manso Correa Machado Dependence aliasing and the control of family-wise error rate in multiple hypothesis testing . . . . . . . . . . . 669--681 Filipe J. Marques and Carlos A. Coelho and Miguel de Carvalho On the distribution of linear combinations of independent Gumbel random variables . . . . . . . . . . . . 683--701
Anonymous Editor's note: 25th Anniversary Special Issue . . . . . . . . . . . . . . . . . 703--703 David J. Hand Statistics and computing: the genesis of data science . . . . . . . . . . . . . . 705--711 Jean-Patrick Baudry and Gilles Celeux EM for mixtures . . . . . . . . . . . . 713--726 Alexandros Beskos and Ajay Jasra and Ege A. Muzaffer and Andrew M. Stuart Sequential Monte Carlo methods for Bayesian elliptic inverse problems . . . 727--737 Ricardo Silva and Alfredo Kalaitzis Bayesian inference via projections . . . 739--753 Bernhard Schölkopf and Krikamol Muandet and Kenji Fukumizu and Stefan Harmeling and Jonas Peters Computing functions of random variables via reproducing kernel Hilbert space representations . . . . . . . . . . . . 755--766 Simon Barthelmé and Nicolas Chopin The Poisson transform for unnormalised statistical models . . . . . . . . . . . 767--780 Panos Toulis and Edoardo M. Airoldi Scalable estimation strategies based on stochastic approximations: classical results and new insights . . . . . . . . 781--795 Sergio Bacallado and Persi Diaconis and Susan Holmes De Finetti Priors using Markov chain Monte Carlo computations . . . . . . . . 797--808 Ying Liu and Andrew Gelman and Tian Zheng Simulation-efficient shortest probability intervals . . . . . . . . . 809--819 Christian Hennig and Chien-Ju Lin Flexible parametric bootstrap for testing homogeneity against clustering and assessing the number of clusters . . 821--833 Peter J. Green and Krzysztof Latuszy\'nski and Marcelo Pereyra and Christian P. Robert Bayesian computation: a summary of the current state, and samples backwards and forwards . . . . . . . . . . . . . . . . 835--862 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Kei Hirose and Michio Yamamoto Sparse estimation via nonconcave penalized likelihood in factor analysis model . . . . . . . . . . . . . . . . . 863--875 Moreno Bevilacqua and Carlo Gaetan Comparing composite likelihood methods based on pairs for spatial Gaussian random fields . . . . . . . . . . . . . 877--892 Antoine Deleforge and Florence Forbes and Radu Horaud High-dimensional regression with Gaussian mixtures and partially-latent response variables . . . . . . . . . . . 893--911 Matthias Borowski and Dennis Busse and Roland Fried Robust online-surveillance of trend-coherence in multivariate data streams: the similar trend monitoring (STM) procedure . . . . . . . . . . . . 913--928 Tommi Mononen A case study of the widely applicable Bayesian information criterion and its optimality . . . . . . . . . . . . . . . 929--940 María Xosé Rodríguez-Álvarez and Dae-Jin Lee and Thomas Kneib and María Durbán and Paul Eilers Fast smoothing parameter separation in multidimensional generalized $P$-splines: the SAP algorithm . . . . . 941--957 José E. Chacón and Tarn Duong Efficient recursive algorithms for functionals based on higher order derivatives of the multivariate Gaussian density . . . . . . . . . . . . . . . . 959--974 Ray-Bing Chen and Shin-Perng Chang and Weichung Wang and Heng-Chih Tung and Weng Kee Wong Minimax optimal designs via particle swarm optimization methods . . . . . . . 975--988 Giang Trinh and Alan Genz Bivariate conditioning approximations for multivariate normal probabilities 989--996 Mathew W. McLean and Giles Hooker and David Ruppert Restricted likelihood ratio tests for linearity in scalar-on-function regression . . . . . . . . . . . . . . . 997--1008 Alfonso Iodice D'Enza and Angelos Markos Low-dimensional tracking of association structures in categorical data . . . . . 1009--1022 David I. Hastie and Silvia Liverani and Sylvia Richardson Sampling from Dirichlet process mixture models with unknown concentration parameter: mixing issues in large data implementations . . . . . . . . . . . . 1023--1037 Andrew Golightly and Daniel A. Henderson and Chris Sherlock Delayed acceptance particle MCMC for exact inference in stochastic kinetic models . . . . . . . . . . . . . . . . . 1039--1055 Anonymous Help & Contacts . . . . . . . . . . . . . ??
Ivan Vujaci\'c and Itai Dattner and Javier González and Ernst Wit Time-course window estimator for ordinary differential equations linear in the parameters . . . . . . . . . . . 1057--1070 Eugen Pircalabelu and Gerda Claeskens and Lourens Waldorp A focused information criterion for graphical models . . . . . . . . . . . . 1071--1092 Minh Khoa Nguyen and Steve Phelps and Wing Lon Ng Simulation based calibration using extended balanced augmented empirical likelihood . . . . . . . . . . . . . . . 1093--1112 Selin Damla Ahipasaoglu A first-order algorithm for the $A$-optimal experimental design problem: a mathematical programming approach . . 1113--1127 Yi Yang and Hui Zou A fast unified algorithm for solving group-lasso penalize learning problems 1129--1141 C. Bouveyron and M. Fauvel and S. Girard Kernel discriminant analysis and clustering with parsimonious Gaussian process models . . . . . . . . . . . . . 1143--1162 Luis Mauricio Castro and Denise Reis Costa and Marcos Oliveira Prates and Victor Hugo Lachos Likelihood-based inference for Tobit confirmatory factor analysis using the multivariate Student-$t$ distribution 1163--1183 Hajo Holzmann and Florian Schwaiger Hidden Markov models with state-dependent mixtures: minimal representation, model testing and applications to clustering . . . . . . . 1185--1200 Christine Keribin and Vincent Brault and Gilles Celeux and Gérard Govaert Estimation and selection for the latent block model on categorical data . . . . 1201--1216 Carlo Albert and Hans R. Künsch and Andreas Scheidegger A simulated annealing approach to approximate Bayes computations . . . . . 1217--1232 G. K. Robinson Practical computing for finite moment log-stable distributions to model financial risk . . . . . . . . . . . . . 1233--1246 Elisabeth Waldmann and Thomas Kneib Variational approximations in geoadditive latent Gaussian regression: mean and quantile regression . . . . . . 1247--1263 Victor Picheny Multiobjective optimization using Gaussian process emulators via stepwise uncertainty reduction . . . . . . . . . 1265--1280 F. J. Rubio Letter to the Editor: On the use of improper priors for the shape parameters of asymmetric exponential power models 1281--1287
Benjamin Hofner and Thomas Kneib and Torsten Hothorn A unified framework of constrained regression . . . . . . . . . . . . . . . 1--14 Daniel Palhazi Cuervo and Peter Goos and Kenneth Sörensen Optimal design of large-scale screening experiments: a critical look at the coordinate-exchange algorithm . . . . . 15--28 P. Alquier and N. Friel and R. Everitt and A. Boland Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels . . . . . . . . . . . . . . . . 29--47 Julian J. Faraway Does data splitting improve prediction? 49--60 E. Gassiat and A. Cleynen and S. Robin Inference in finite state space non parametric Hidden Markov Models and applications . . . . . . . . . . . . . . 61--71 Felix Heinzl and Gerhard Tutz Additive mixed models with approximate Dirichlet process mixtures: the EM approach . . . . . . . . . . . . . . . . 73--92 E. Dubossarsky and J. H. Friedman and J. T. Ormerod and M. P. Wand Wavelet-based gradient boosting . . . . 93--105 Giacomo Aletti and Caterina May and Chiara Tommasi KL-optimum designs: theoretical properties and practical computation . . 107--117 Jacob Gagnon and Hua Liang and Anna Liu Spherical radial approximation for nested mixed effects models . . . . . . 119--130 Sungwan Bang and HyungJun Cho and Myoungshic Jhun Simultaneous estimation for non-crossing multiple quantile regression with right censored data . . . . . . . . . . . . . 131--147 K. Chowdhary and H. N. Najm Data free inference with processed data products . . . . . . . . . . . . . . . . 149--169 Dennis Prangle Lazy ABC . . . . . . . . . . . . . . . . 171--185 Noboru Nomura Evaluation of Gaussian orthant probabilities based on orthogonal projections to subspaces . . . . . . . . 187--197 Chong You and Samuel Müller and John T. Ormerod On generalized degrees of freedom with application in linear mixed models selection . . . . . . . . . . . . . . . 199--210 Eric Simonnet Combinatorial analysis of the adaptive last particle method . . . . . . . . . . 211--230 Junshan Wang and Ajay Jasra Monte Carlo algorithms for computing $ \alpha $-permanents . . . . . . . . . . 231--248 Bei Wei and Stephen M. S. Lee and Xiyuan Wu Stochastically optimal bootstrap sample size for shrinkage-type statistics . . . 249--262 A. Cleynen and S. Robin Comparing change-point location in independent series . . . . . . . . . . . 263--276 Frederick Kin Hing Phoa and Tai-Chi Wang and Shu-Ching Lin A search of maximum generalized resolution quaternary-code designs via integer linear programming . . . . . . . 277--283 Vivian Viallon and Sophie Lambert-Lacroix and Hölger Hoefling and Franck Picard On the robustness of the generalized fused lasso to prior specifications . . 285--301 Gertraud Malsiner-Walli and Sylvia Frühwirth-Schnatter and Bettina Grün Model-based clustering based on sparse finite Gaussian mixtures . . . . . . . . 303--324 F. Critchley and P. Marriott Computing with Fisher geodesics and extended exponential families . . . . . 325--332 Silia Vitoratou and Ioannis Ntzoufras and Irini Moustaki Explaining the behavior of joint and marginal Monte Carlo estimators in latent variable models with independence assumptions . . . . . . . . . . . . . . 333--348 Christopher J. Fallaize and Theodore Kypraios Exact Bayesian inference for the Bingham distribution . . . . . . . . . . . . . . 349--360 Minh-Ngoc Tran and Michael K. Pitt and Robert Kohn Adaptive Metropolis--Hastings sampling using reversible dependent mixture proposals . . . . . . . . . . . . . . . 361--381 Johannes Buchner A statistical test for Nested Sampling algorithms . . . . . . . . . . . . . . . 383--392 Anindya Bhadra and Edward L. Ionides Adaptive particle allocation in iterated sequential Monte Carlo via approximating meta-models . . . . . . . . . . . . . . 393--407 Luo Xiao and Vadim Zipunnikov and David Ruppert and Ciprian Crainiceanu Fast covariance estimation for high-dimensional functional data . . . . 409--421 J. E. Griffin An adaptive truncation method for inference in Bayesian nonparametric models . . . . . . . . . . . . . . . . . 423--441 Caio L. N. Azevedo and Jean-Paul Fox and Dalton F. Andrade Bayesian longitudinal item response modeling with restricted covariance pattern structures . . . . . . . . . . . 443--460 Lisha Chen and Jianhua Z. Huang Sparse reduced-rank regression with covariance estimation . . . . . . . . . 461--470 Seppo Pulkkinen Nonlinear kernel density principal component analysis with application to climate data . . . . . . . . . . . . . . 471--492 Lin Zhang and Abhra Sarkar and Bani K. Mallick Bayesian sparse covariance decomposition with a graphical structure . . . . . . . 493--510 Arthur White and Jason Wyse and Thomas Brendan Murphy Bayesian variable selection for latent class analysis using a collapsed Gibbs sampler . . . . . . . . . . . . . . . . 511--527 Monia Ranalli and Roberto Rocci Mixture models for ordinal data: a pairwise likelihood approach . . . . . . 529--547 Jean-Baptiste Durand and Yann Guédon Localizing the latent structure canonical uncertainty: entropy profiles for hidden Markov models . . . . . . . . 549--567 Jean-Baptiste Durand and Yann Guédon Erratum to: Localizing the latent structure canonical uncertainty: entropy profiles for hidden Markov models . . . 569--570 François Caron Book Review: \booktitleNonlinear Time Series: Theory, methods, and applications with R examples, by Randal Douc, Eric Moulines, David S. Stoffer 571--572
Sharon X. Lee and Geoffrey J. McLachlan Finite mixtures of canonical fundamental skew $t$-distributions . . . . . . . . . 573--589 Radislav Vaisman and Zdravko I. Botev and Ad Ridder Sequential Monte Carlo for counting vertex covers in general graphs . . . . 591--607 Chun Yip Yau and Kin Wai Chan New recursive estimators of the time-average variance constant . . . . . 609--627 Yanhong Wang and Yixin Fang and Junhui Wang Sparse optimal discriminant clustering 629--639 Raffaele Argiento and Ilaria Bianchini and Alessandra Guglielmi A blocked Gibbs sampler for NGG-mixture models via a priori truncation . . . . . 641--661 Sabine Hug and Michael Schwarzfischer and Jan Hasenauer and Carsten Marr and Fabian J. Theis An adaptive scheduling scheme for calculating Bayes factors with thermodynamic integration using Simpson's rule . . . . . . . . . . . . . 663--677 Erlis Ruli and Nicola Sartori and Laura Ventura Approximate Bayesian computation with composite score functions . . . . . . . 679--692 Fortunato Pesarin and Luigi Salmaso and Eleonora Carrozzo and Rosa Arboretti Union-intersection permutation solution for two-sample equivalence testing . . . 693--701 Amir Ahmadi-Javid and Asghar Moeini An economical acceptance-rejection algorithm for uniform random variate generation over constrained simplexes 703--713 Julie Josse and Sylvain Sardy Adaptive shrinkage of singular values 715--724 Md Hasinur Rahaman Khan and J. Ewart H. Shaw Variable selection for survival data with a class of adaptive elastic net techniques . . . . . . . . . . . . . . . 725--741 A. Martín Andrés and M. Álvarez Hernández Erratum to: Two-tailed approximate confidence intervals for the ratio of proportions . . . . . . . . . . . . . . 743--744
Marcelo Pereyra Proximal Markov chain Monte Carlo algorithms . . . . . . . . . . . . . . . 745--760 David A. Spade A computational procedure for estimation of the mixing time of the random-scan Metropolis algorithm . . . . . . . . . . 761--781 Émeline Perthame and Chloé Friguet and David Causeur Stability of feature selection in classification issues for high-dimensional correlated data . . . . 783--796 Chris J. Oates and Jim Q. Smith and Sach Mukherjee and James Cussens Exact estimation of multiple directed acyclic graphs . . . . . . . . . . . . . 797--811 Clifford Anderson-Bergman and Yaming Yu Computing the log concave NPMLE for interval censored data . . . . . . . . . 813--826 Anindya Bhadra and Raymond J. Carroll Exact sampling of the unobserved covariates in Bayesian spline models for measurement error problems . . . . . . . 827--840 Nadja Klein and Thomas Kneib Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach . . 841--860 Md. Abul Hasnat and Olivier Alata and Alain Trémeau Model-based hierarchical clustering with Bregman divergences and Fishers mixture model: application to depth image analysis . . . . . . . . . . . . . . . . 861--880 Longhai Li and Shi Qiu and Bei Zhang and Cindy X. Feng Approximating cross-validatory predictive evaluation in Bayesian latent variable models with integrated IS and WAIC . . . . . . . . . . . . . . . . . . 881--897 James Ridgway Computation of Gaussian orthant probabilities in high dimension . . . . 899--916 Dean A. Bodenham and Niall M. Adams A comparison of efficient approximations for a weighted sum of chi-squared random variables . . . . . . . . . . . . . . . 917--928
Christophe Biernacki and Julien Jacques Model-based clustering of multivariate ordinal data relying on a stochastic binary search algorithm . . . . . . . . 929--943 Giles Hooker and Steven Roberts Maximal autocorrelation functions in functional data analysis . . . . . . . . 945--950 Mateusz Krzysztof Lacki and Blazej Miasojedow State-dependent swap strategies and automatic reduction of number of temperatures in adaptive parallel tempering algorithm . . . . . . . . . . 951--964 Gildas Mazo and Stéphane Girard and Florence Forbes A flexible and tractable class of one-factor copulas . . . . . . . . . . . 965--979 Rosalba Radice and Giampiero Marra and Ma\lgorzata Wojty\'s Copula regression spline models for binary outcomes . . . . . . . . . . . . 981--995 Xingyu Tang and Heng Lian Mean and quantile boosting for partially linear additive models . . . . . . . . . 997--1008 Tore Selland Kleppe and Hans J. Skaug Bandwidth selection in pre-smoothed particle filters . . . . . . . . . . . . 1009--1024 Giuliano Galimberti and Elena Scardovi and Gabriele Soffritti Using mixtures in seemingly unrelated linear regression models with non-normal errors . . . . . . . . . . . . . . . . . 1025--1038 Gerhard Tutz and Dominik Koch Improved nearest neighbor classifiers by weighting and selection of predictors 1039--1057 Andre Beinrucker and Ürün Dogan and Gilles Blanchard Extensions of stability selection using subsamples of observations and covariates . . . . . . . . . . . . . . . 1059--1077 Ioannis Kosmidis and Dimitris Karlis Model-based clustering using copulas with applications . . . . . . . . . . . 1079--1099 David P. Hofmeyr and Nicos G. Pavlidis and Idris A. Eckley Divisive clustering of high dimensional data streams . . . . . . . . . . . . . . 1101--1120 J. M. McGree and C. C. Drovandi and G. White and A. N. Pettitt A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design . . . . . . . 1121--1136
Michael A. Spence and Paul G. Blackwell Coupling random inputs for parameter estimation in complex models . . . . . . 1137--1146 Nicholas A. Heard and Melissa J. M. Turcotte Convergence of Monte Carlo distribution estimates from rival samplers . . . . . 1147--1161 C. Tommasi and R. Martín-Martín and J. López-Fidalgo Max-min optimal discriminating designs for several statistical models . . . . . 1163--1172 Pierre Latouche and Stéphane Robin Variational Bayes model averaging for graphon functions and motif frequencies inference in $W$-graph models . . . . . 1173--1185 F. J. Medina-Aguayo and A. Lee and G. O. Roberts Stability of noisy Metropolis--Hastings 1187--1211 Joris Bierkens Non-reversible Metropolis--Hastings . . 1213--1228 Eric Schmitt and Kaveh Vakili The FastHCS algorithm for robust PCA . . 1229--1242 Linda S. L. Tan and Victor M. H. Ong and David J. Nott and Ajay Jasra Variational inference for sparse spectrum Gaussian process regression . . 1243--1261 Wagner Barreto-Souza and Alexandre B. Simas General mixed Poisson regression models with varying dispersion . . . . . . . . 1263--1280 Benjamin M. Gyori and Daniel Paulin Hypothesis testing for Markov chain Monte Carlo . . . . . . . . . . . . . . 1281--1292 Paul Fearnhead and Loukia Meligkotsidou Augmentation schemes for particle MCMC 1293--1306 Arthur Pewsey and Shogo Kato Parametric bootstrap goodness-of-fit testing for Wehrly--Johnson bivariate circular distributions . . . . . . . . . 1307--1317 Nathaniel E. Helwig Efficient estimation of variance components in nonparametric mixed-effects models with large samples 1319--1336
Anonymous Editor's note: special section on Bayesian Nonparametrics . . . . . . . . 1--1 Julyan Arbel and Igor Prünster A moment-matching Ferguson & Klass algorithm . . . . . . . . . . . . . . . 3--17 Sanmitra Ghosh and Srinandan Dasmahapatra and Koushik Maharatna Fast approximate Bayesian computation for estimating parameters in differential equations . . . . . . . . . 19--38 William Cipolli III and Timothy Hanson Computationally tractable approximate and smoothed Pólya trees . . . . . . . . 39--51 William Cipolli III and Timothy Hanson Erratum to: Computationally tractable approximate and smoothed Pólya trees . . 53--53 Eugen Pircalabelu and Gerda Claeskens and Ir\`ene Gijbels Copula directed acyclic graphs . . . . . 55--78 Leo N. Geppert and Katja Ickstadt and Alexander Munteanu and Jens Quedenfeld and Christian Sohler Random projections for Bayesian regression . . . . . . . . . . . . . . . 79--101 Tao Wang and Xuerong Meggie Wen and Lixing Zhu Multiple-population shrinkage estimation via sliced inverse regression . . . . . 103--114 Tomi Janhunen and Martin Gebser and Jussi Rintanen and Henrik Nyman and Johan Pensar and Jukka Corander Learning discrete decomposable graphical models via constraint optimization . . . 115--130 J. E. Griffin Sequential Monte Carlo methods for mixtures with normalized random measures with independent increments priors . . . 131--145 Gersende Fort and Benjamin Jourdain and Tony Leli\`evre and Gabriel Stoltz Self-healing umbrella sampling: convergence and efficiency . . . . . . . 147--168 Jean-Michel Bécu and Yves Grandvalet and Christophe Ambroise and Cyril Dalmasso Beyond support in two-stage variable selection . . . . . . . . . . . . . . . 169--179 Ting Yuan and Junhui Wang Reduced-rank multi-label classification 181--191 J. M. Alonso-Revenga and N. Martín and L. Pardo New improved estimators for overdispersion in models with clustered multinomial data and unequal cluster sizes . . . . . . . . . . . . . . . . . 193--217 Clément Walter Point process-based Monte Carlo estimation . . . . . . . . . . . . . . . 219--236 Linda S. L. Tan Stochastic variational inference for large-scale discrete choice models using adaptive batch sizes . . . . . . . . . . 237--257 Roland Langrock and Thomas Kneib and Richard Glennie and Théo Michelot Markov-switching generalized additive models . . . . . . . . . . . . . . . . . 259--270 Linda Schulze Waltrup and Göran Kauermann Smooth expectiles for panel data using penalized splines . . . . . . . . . . . 271--282 Francesco Donat and Giampiero Marra Semi-parametric bivariate polychotomous ordinal regression . . . . . . . . . . . 283--299
Marie Lilleborge and Jo Eidsvik Efficient designs for Bayesian networks with sub-tree bounds . . . . . . . . . . 301--318 François Wahl and Cécile Mercadier and Céline Helbert A standardized distance-based index to assess the quality of space-filling designs . . . . . . . . . . . . . . . . 319--329 Osnat Stramer and Xiaoyu Shen and Matthew Bognar Bayesian inference for Heston--STAR models . . . . . . . . . . . . . . . . . 331--348 Stella Hadjiantoni and Erricos John Kontoghiorghes Estimating large-scale general linear and seemingly unrelated regressions models after deleting observations . . . 349--361 Matthias Katzfuss and Dorit Hammerling Parallel inference for massive distributed spatial data using low-rank models . . . . . . . . . . . . . . . . . 363--375 L. A. García-Escudero and A. Gordaliza and F. Greselin and S. Ingrassia and A. Mayo-Iscar Robust estimation of mixtures of regressions with random covariates, via trimming and constraints . . . . . . . . 377--402 Richard G. Everitt and Adam M. Johansen and Ellen Rowing and Melina Evdemon-Hogan Bayesian model comparison with un-normalised likelihoods . . . . . . . 403--422 Yongtao Cao and Byran J. Smucker and Timothy J. Robinson A hybrid elitist pareto-based coordinate exchange algorithm for constructing multi-criteria optimal experimental designs . . . . . . . . . . . . . . . . 423--437 Stephen G. Walker A Laplace transform inversion method for probability distribution functions . . . 439--448 Fadlalla G. Elfadaly and Paul H. Garthwaite Eliciting Dirichlet and Gaussian copula prior distributions for multinomial models . . . . . . . . . . . . . . . . . 449--467 Matteo Borrotti and Francesco Sambo and Kalliopi Mylona and Steven Gilmour A multi-objective coordinate-exchange two-phase local search algorithm for multi-stratum experiments . . . . . . . 469--481 Sy Han Chiou and Gongjun Xu Rank-based estimation for semiparametric accelerated failure time model under length-biased sampling . . . . . . . . . 483--500 Vincent Audigier and François Husson and Julie Josse MIMCA: multiple imputation for categorical variables with multiple correspondence analysis . . . . . . . . 501--518 Robert Maidstone and Toby Hocking and Guillem Rigaill and Paul Fearnhead On optimal multiple changepoint algorithms for large data . . . . . . . 519--533 Guosheng Cheng and Xingxiang Li and Peng Lai and Fengli Song and Jun Yu Robust rank screening for ultrahigh dimensional discriminant analysis . . . 535--545 Marco Alf\`o and Nicola Salvati and M. Giovanna Ranallli Finite mixtures of quantile and $M$-quantile regression models . . . . . 547--570 Yan Yu and Chaojiang Wu and Yuankun Zhang Penalised spline estimation for generalised partially linear single-index models . . . . . . . . . . 571--582
Luke Bornn and Natesh S. Pillai and Aaron Smith and Dawn Woodard The use of a single pseudo-sample in approximate Bayesian computation . . . . 583--590 Vahed Maroufy and Paul Marriott Mixture models: building a parameter space . . . . . . . . . . . . . . . . . 591--597 L. Martino and V. Elvira and D. Luengo and J. Corander Layered adaptive importance sampling . . 599--623 Sergio Amaral and Douglas Allaire and Karen Willcox Optimal $ L_2 $-norm empirical importance weights for the change of probability measure . . . . . . . . . . 625--643 Elvira Romano and Antonio Balzanella and Rosanna Verde Spatial variability clustering for spatially dependent functional data . . 645--658 Baptiste Gregorutti and Bertrand Michel and Philippe Saint-Pierre Correlation and variable importance in random forests . . . . . . . . . . . . . 659--678 Sarat C. Dass and Jaeyong Lee and Kyoungjae Lee and Jonghun Park Laplace based approximate posterior inference for differential equation models . . . . . . . . . . . . . . . . . 679--698 Luc Devroye and Claude Gravel The expected bit complexity of the von Neumann rejection algorithm . . . . . . 699--710 Juho Piironen and Aki Vehtari Comparison of Bayesian predictive methods for model selection . . . . . . 711--735 Petter Arnesen and Håkon Tjelmeland Prior specification of neighbourhood and interaction structure in binary Markov random fields . . . . . . . . . . . . . 737--756 Jérémy Magnanensi and Frédéric Bertrand and Myriam Maumy-Bertrand and Nicolas Meyer A new universal resample-stable bootstrap-based stopping criterion for PLS component construction . . . . . . . 757--774 Christine M. O'Keefe and Tim Ayre and Sebastien Lucie and Atikur R. Khan and Soomin Song and Soonmin Kwon Perturbed robust linear estimating equations for confidentiality protection in remote analysis . . . . . . . . . . . 775--787 Julien Chiquet and Tristan Mary-Huard and Stéphane Robin Structured regularization for conditional Gaussian graphical models 789--804 Félix Camirand Lemyre and Jean-François Quessy Multiplier bootstrap methods for conditional distributions . . . . . . . 805--821 Axel Gandy and Georg Hahn QuickMMCTest: quick multiple Monte Carlo testing . . . . . . . . . . . . . . . . 823--832 N. Friel and J. P. McKeone and C. J. Oates and A. N. Pettitt Investigation of the widely applicable Bayesian information criterion . . . . . 833--844 Mercedes Esteban-Bravo and Agata Leszkiewicz and Jose M. Vidal-Sanz Exact optimal experimental designs with constraints . . . . . . . . . . . . . . 845--863
Abdallah Mkhadri and Mohamed Ouhourane and Karim Oualkacha A coordinate descent algorithm for computing penalized smooth quantile regression . . . . . . . . . . . . . . . 865--883 Gavin A. Whitaker and Andrew Golightly and Richard J. Boys and Chris Sherlock Improved bridge constructs for stochastic differential equations . . . 885--900 Houying Zhu and Josef Dick A discrepancy bound for deterministic acceptance-rejection samplers beyond $ N^{-1 / 2} $ in dimension $1$ . . . . . 901--911 Sarah Brockhaus and Michael Melcher and Friedrich Leisch and Sonja Greven Boosting flexible functional regression models with a high number of functional historical effects . . . . . . . . . . . 913--926 Georgios Karagiannis and Bledar A. Konomi and Guang Lin and Faming Liang Parallel and interacting stochastic approximation annealing algorithms for global optimisation . . . . . . . . . . 927--945 Tingyou Zhou and Liping Zhu Model-free feature screening for ultrahigh dimensional censored regression . . . . . . . . . . . . . . . 947--961 Sonia Migliorati and Andrea Ongaro and Gianna S. Monti A structured Dirichlet mixture model for compositional data: inferential and applicative issues . . . . . . . . . . . 963--983 Simon N. Wood P-splines with derivative based penalties and tensor product smoothing of unevenly distributed data . . . . . . 985--989 Anastasis Georgoulas and Jane Hillston and Guido Sanguinetti Unbiased Bayesian inference for population Markov jump processes via random truncations . . . . . . . . . . . 991--1002 Andrej Aderhold and Dirk Husmeier and Marco Grzegorczyk Approximate Bayesian inference in semi-mechanistic models . . . . . . . . 1003--1040 Chun Yip Yau and Tsz Shing Hui LARS-type algorithm for group lasso . . 1041--1048 Matthieu Marbac and Mohammed Sedki Variable selection for model-based clustering using the integrated complete-data likelihood . . . . . . . . 1049--1063 Patrick R. Conrad and Mark Girolami and Simo Särkkä and Andrew Stuart and Konstantinos Zygalakis Statistical analysis of differential equations: introducing probability measures on numerical solutions . . . . 1065--1082 Thomas Muehlenstaedt and Jana Fruth and Olivier Roustant Computer experiments with functional inputs and scalar outputs by a norm-based approach . . . . . . . . . . 1083--1097 Bráulio M. Veloso and Thais R. Correa and Marcos O. Prates and Gabriel F. Oliveira and Andréa I. Tavares MAD--STEC: a method for multiple automatic detection of space-time emerging clusters . . . . . . . . . . . 1099--1110 Pierre Barbillon and Célia Barthélémy and Adeline Samson Parameter estimation of complex mixed models based on meta-model approach . . 1111--1128 Sarah L. Taylor and Idris A. Eckley and Matthew A. Nunes Multivariate locally stationary $2$D wavelet processes with application to colour texture analysis . . . . . . . . 1129--1143
Charlotte Laclau and Mohamed Nadif Diagonal latent block model for binary data . . . . . . . . . . . . . . . . . . 1145--1163 Silia Vitoratou and Ioannis Ntzoufras Thermodynamic Bayesian model comparison 1165--1180 Lu-Hung Chen and Ci-Ren Jiang Multi-dimensional functional principal component analysis . . . . . . . . . . . 1181--1192 Xuehu Zhu and Xu Guo and Lixing Zhu An adaptive-to-model test for partially parametric single-index models . . . . . 1193--1204 Finale Doshi-Velez and Sinead A. Williamson Restricted Indian buffet processes . . . 1205--1223 Radu S. Stoica and Anne Philippe and Pablo Gregori and Jorge Mateu ABC Shadow algorithm: a tool for statistical analysis of spatial patterns 1225--1238 Tomás Mrkvicka and Mari Myllymäki and Ute Hahn Multiple Monte Carlo testing, with applications in spatial point processes 1239--1255 Dean A. Bodenham and Niall M. Adams Continuous monitoring for changepoints in data streams using adaptive estimation . . . . . . . . . . . . . . . 1257--1270 Haakon Michael Austad and Håkon Tjelmeland Approximate computations for binary Markov random fields and their use in Bayesian models . . . . . . . . . . . . 1271--1292 Kaylea Haynes and Paul Fearnhead and Idris A. Eckley A computationally efficient nonparametric approach for changepoint detection . . . . . . . . . . . . . . . 1293--1305 Mathieu Cambou and Marius Hofert and Christiane Lemieux Quasi-random numbers for copula models 1307--1329 L. Schwaller and S. Robin Exact Bayesian inference for off-line change-point detection in tree-structured graphical models . . . . 1331--1345 Shanshan Wang and Liming Xiang Penalized empirical likelihood inference for sparse additive hazards regression with a diverging number of covariates 1347--1364 Guillermo Julián-Moreno and Jorge E. López de Vergara and Iván González and Luis de Pedro and Javier Royuela-del-Val and Federico Simmross-Wattenberg Fast parallel $ \alpha $-stable distribution function evaluation and parameter estimation using OpenCL in GPGPUs . . . . . . . . . . . . . . . . . 1365--1382 Maarten Jansen and Mohamed Amghar Multiscale local polynomial decompositions using bandwidths as scales . . . . . . . . . . . . . . . . . 1383--1399 Bingqing Lin and Qihua Wang and Jun Zhang and Zhen Pang Stable prediction in high-dimensional linear models . . . . . . . . . . . . . 1401--1412 Aki Vehtari and Andrew Gelman and Jonah Gabry Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC . . . . . . . . . . . . . . . . . . 1413--1432 Aki Vehtari and Andrew Gelman and Jonah Gabry Erratum to: Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC . . . . . . . 1433--1433
Brian Bader and Jun Yan and Xuebin Zhang Automated selection of $r$ for the $r$ largest order statistics approach with adjustment for sequential testing . . . 1435--1451 Marina I. Knight and Guy P. Nason and Matthew A. Nunes A wavelet lifting approach to long-memory estimation . . . . . . . . . 1453--1471 Cheng Zhang and Babak Shahbaba and Hongkai Zhao Hamiltonian Monte Carlo acceleration using surrogate functions with random bases . . . . . . . . . . . . . . . . . 1473--1490 Mark R. Bass and Sujit K. Sahu A comparison of centring parameterisations of Gaussian process-based models for Bayesian computation using MCMC . . . . . . . . . 1491--1512 Nino Kordzakhia and Alexander Novikov and Bernard Ycart Approximations for weighted Kolmogorov--Smirnov distributions via boundary crossing probabilities . . . . 1513--1523 Maria DeYoreo and Athanasios Kottas A Bayesian nonparametric Markovian model for non-stationary time series . . . . . 1525--1538 Elisabeth Waldmann and Fabian Sobotka and Thomas Kneib Bayesian regularisation in geoadditive expectile regression . . . . . . . . . . 1539--1553 Matthew M. Dunlop and Marco A. Iglesias and Andrew M. Stuart Hierarchical Bayesian level set inversion . . . . . . . . . . . . . . . 1555--1584 Andrew C. Titman Non-parametric maximum likelihood estimation of interval-censored failure time data subject to misclassification 1585--1593 Håkon Otneim and Dag Tjòstheim The locally Gaussian density estimator for multivariate data . . . . . . . . . 1595--1616 Allou Samé and Gérard Govaert Segmental dynamic factor analysis for time series of curves . . . . . . . . . 1617--1637 Chong Liu and Surajit Ray and Giles Hooker Functional principal component analysis of spatially correlated data . . . . . . 1639--1654 B. Pérez and I. Molina and A. Thieler and R. Fried and D. Peña Fast and robust estimators of variance components in the nested error model . . 1655--1675 Dao Nguyen and Edward L. Ionides A second-order iterated smoothing algorithm . . . . . . . . . . . . . . . 1677--1692
Han Lin Shang Bootstrap methods for stationary functional time series . . . . . . . . . 1--10 C. Bouveyron and P. Latouche and R. Zreik The stochastic topic block model for the clustering of vertices in networks with textual edges . . . . . . . . . . . . . 11--31 Tao Wang and Mengjie Chen and Hongyu Zhao and Lixing Zhu Estimating a sparse reduction for general regression in high dimensions 33--46 Ajay Jasra and Kengo Kamatani and Prince Peprah Osei and Yan Zhou Multilevel particle filters: normalizing constant estimation . . . . . . . . . . 47--60 Nadhir Ben Rached and Fatma Benkhelifa and Abla Kammoun and Mohamed-Slim Alouini and Raul Tempone On the generalization of the hazard rate twisting-based simulation approach . . . 61--75 Giles Hooker and Lucas Mentch Bootstrap bias corrections for ensemble methods . . . . . . . . . . . . . . . . 77--86 Robert Richardson and Athanasios Kottas and Bruno Sansó Bayesian non-parametric modeling for integro-difference equations . . . . . . 87--101 Sera Aylin Cakiroglu Optimal regular graph designs . . . . . 103--112 Qinyi Zhang and Sarah Filippi and Arthur Gretton and Dino Sejdinovic Large-scale kernel methods for independence testing . . . . . . . . . . 113--130 Jere Koskela and Dario Span\`o and Paul A. Jenkins Inference and rare event simulation for stopped Markov processes via reverse-time sequential Monte Carlo . . 131--144 Giuliano Galimberti and Annamaria Manisi and Gabriele Soffritti Modelling the role of variables in model-based cluster analysis . . . . . . 145--169 Sebastian Ament and Michael O'Neil Accurate and efficient numerical calculation of stable densities via optimized quadrature and asymptotics . . 171--185 Yong Wang and Shabnam Fani Nonparametric maximum likelihood computation of a $U$-shaped hazard function . . . . . . . . . . . . . . . . 187--200 Alberto Gascón and Eugenio F. Sánchez-Úbeda Automatic specification of piecewise linear additive models: application to forecasting natural gas demand . . . . . 201--217 Mimi Zhang and Tim Bedford Vine copula approximation: a generic method for coping with conditional dependence . . . . . . . . . . . . . . . 219--237 F. J. Medina-Aguayo and A. Lee and G. O. Roberts Erratum to: Stability of noisy Metropolis--Hastings . . . . . . . . . . 239--239
Douglas P. Wiens I-robust and D-robust designs on a finite design space . . . . . . . . . . 241--258 Linda S. L. Tan and David J. Nott Gaussian variational approximation with sparse precision matrices . . . . . . . 259--275 Benedict Leimkuhler and Charles Matthews and Jonathan Weare Ensemble preconditioning for Markov chain Monte Carlo simulation . . . . . . 277--290 Ben Norwood and Rebecca Killick Long memory and changepoint models: a spectral classification procedure . . . 291--302 Håkon Otneim and Dag Tjòstheim Conditional density estimation using the local Gaussian correlation . . . . . . . 303--321 Matthias Killiches and Daniel Kraus and Claudia Czado Model distances for vine copulas in high dimensions . . . . . . . . . . . . . . . 323--341 Antony M. Overstall and James M. McGree and Christopher C. Drovandi An approach for finding fully Bayesian optimal designs using normal-based approximations to loss functions . . . . 343--358 Lucia Paci and Francesco Finazzi Dynamic model-based clustering for spatio-temporal data . . . . . . . . . . 359--374 Russell B. Millar Conditional vs marginal estimation of the predictive loss of hierarchical models using WAIC and cross-validation 375--385 Christian Schellhase and Fabian Spanhel Estimating non-simplified vine copulas using penalized splines . . . . . . . . 387--409 Michael U. Gutmann and Ritabrata Dutta and Samuel Kaski and Jukka Corander Likelihood-free inference via classification . . . . . . . . . . . . . 411--425 Ferran Espuny-Pujol and Karyn Morrissey and Paul Williamson A global optimisation approach to range-restricted survey calibration . . 427--439 Belmiro P. M. Duarte and Weng Kee Wong and Holger Dette Adaptive grid semidefinite programming for finding optimal designs . . . . . . 441--460 Deborshee Sen and Alexandre H. Thiery and Ajay Jasra On coupling particle filter trajectories 461--475 Francesco Dotto and Alessio Farcomeni and Luis Angel García-Escudero and Agustín Mayo-Iscar A reweighting approach to robust clustering . . . . . . . . . . . . . . . 477--493
Lan Jiang and Sumeetpal S. Singh Tracking multiple moving objects in images using Markov Chain Monte Carlo 495--510 Luo Xiao and Cai Li and William Checkley and Ciprian Crainiceanu Fast covariance estimation for sparse functional data . . . . . . . . . . . . 511--522 Luo Xiao and Cai Li and William Checkley and Ciprian Crainiceanu Erratum to: Fast covariance estimation for sparse functional data . . . . . . . 523--523 Sabrina Vettori and Raphaël Huser and Marc G. Genton A comparison of dependence function estimators in multivariate extremes . . 525--538 David Hand and Peter Christen A note on using the $F$-measure for evaluating record linkage algorithms . . 539--547 Matteo Fasiolo and Flávio Eler de Melo and Simon Maskell Langevin incremental mixture importance sampling . . . . . . . . . . . . . . . . 549--561 Alexey Lindo and Sergei Zuyev and Serik Sagitov Nonparametric estimation for compound Poisson process via variational analysis on measures . . . . . . . . . . . . . . 563--577 E. Charitidou and D. Fouskakis and I. Ntzoufras Objective Bayesian transformation and variable selection using default Bayes factors . . . . . . . . . . . . . . . . 579--594 Charalampos Chanialidis and Ludger Evers and Tereza Neocleous and Agostino Nobile Efficient Bayesian inference for COM--Poisson regression models . . . . . 595--608 Daniel W. Meyer Density estimation with distribution element trees . . . . . . . . . . . . . 609--632 Rohan Shah and Dirk P. Kroese Without-replacement sampling for particle methods on finite state spaces 633--652 François Kamper and Johan A. du Preez and Sarel J. Steel and Stephan Wagner Regularized Gaussian belief propagation 653--672 Janek Thomas and Andreas Mayr and Bernd Bischl and Matthias Schmid and Adam Smith and Benjamin Hofner Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates . . . . . . . . . . . . . . . . 673--687 P. J. Paine and S. P. Preston and M. Tsagris and Andrew T. A. Wood An elliptically symmetric angular Gaussian distribution . . . . . . . . . 689--697 Zhi-Yong Chen and Hai-Bin Wang Latent single-index models for ordinal data . . . . . . . . . . . . . . . . . . 699--711 Yunlong Nie and Liangliang Wang and Baisen Liu and Jiguo Cao Supervised functional principal component analysis . . . . . . . . . . . 713--723
Lluís Antoni Jiménez Rugama and Laurent Gilquin Reliable error estimation for Sobol' indices . . . . . . . . . . . . . . . . 725--738 Erin R. Leatherman and Thomas J. Santner and Angela M. Dean Computer experiment designs for accurate prediction . . . . . . . . . . . . . . . 739--751 Hassan Pazira and Luigi Augugliaro and Ernst Wit Extended differential geometric LARS for high-dimensional GLMs with general dispersion parameter . . . . . . . . . . 753--774 Junlong Zhao and Hongyu Zhao and Lixing Zhu Pivotal variable detection of the covariance matrix and its application to high-dimensional factor models . . . . . 775--793 Tore Selland Kleppe Modified Cholesky Riemann Manifold Hamiltonian Monte Carlo: exploiting sparsity for fast sampling of high-dimensional targets . . . . . . . . 795--817 Dennis Prangle and Richard G. Everitt and Theodore Kypraios A rare event approach to high-dimensional approximate Bayesian computation . . . . . . . . . . . . . . 819--834 A. Kume and T. Sei On the exact maximum likelihood inference of Fisher--Bingham distributions using an adjusted holonomic gradient method . . . . . . . 835--847 Didier Rulli\`ere and Nicolas Durrande and François Bachoc and Clément Chevalier Nested Kriging predictions for datasets with a large number of observations . . 849--867 Belinda Hernández and Adrian E. Raftery and Stephen R. Pennington and Andrew C. Parnell Bayesian Additive Regression Trees using Bayesian model averaging . . . . . . . . 869--890 Clement Lee and Andrew Garbett and Darren J. Wilkinson A network epidemic model for online community commissioning data . . . . . . 891--904 Magali Champion and Victor Picheny and Matthieu Vignes Inferring large graphs using $ \ell_1 $-penalized likelihood . . . . . . . . . 905--921 Abdul-Lateef Haji-Ali and Raúl Tempone Multilevel and Multi-index Monte Carlo methods for the McKean--Vlasov equation 923--935 Tilman M. Davies and Adrian Baddeley Fast computation of spatially adaptive kernel estimates . . . . . . . . . . . . 937--956 Leonardo Egidi and Roberta Pappad\`a and Francesco Pauli and Nicola Torelli Relabelling in Bayesian mixture models by pivotal units . . . . . . . . . . . . 957--969 Victor M. H. Ong and David J. Nott and Minh-Ngoc Tran and Scott A. Sisson and Christopher C. Drovandi Variational Bayes with synthetic likelihood . . . . . . . . . . . . . . . 971--988
Marco Corneli and Pierre Latouche and Fabrice Rossi Multiple change points detection and clustering in dynamic networks . . . . . 989--1007 Garritt L. Page and Fernando A. Quintana Calibrating covariate informed product partition models . . . . . . . . . . . . 1009--1031 Virgilio Gómez-Rubio and Håvard Rue Markov chain Monte Carlo with the Integrated Nested Laplace Approximation 1033--1051 Maria Myrto Folia and Magnus Rattray Trajectory inference and parameter estimation in stochastic models with temporally aggregated data . . . . . . . 1053--1072 Shihao Yang and Yang Chen and Espen Bernton and Jun S. Liu On parallelizable Markov chain Monte Carlo algorithms with waste-recycling 1073--1081 Xin Wang and Vivekananda Roy and Zhengyuan Zhu A new algorithm to estimate monotone nonparametric link functions and a comparison with parametric approach . . 1083--1094 Fanghu Dong and Guosheng Yin Maximum likelihood estimation for incomplete multinomial data via the weaver algorithm . . . . . . . . . . . . 1095--1117
Jonathan Law and Darren J. Wilkinson Composable models for online Bayesian analysis of streaming data . . . . . . . 1119--1137 J. D. B. Nelson and A. J. Gibberd and C. Nafornita and N. Kingsbury The locally stationary dual-tree complex wavelet model . . . . . . . . . . . . . 1139--1154 Frédéric J. P. Richard Anisotropy of Hölder Gaussian random fields: characterization, estimation, and application to image textures . . . 1155--1168 Riccardo Rastelli and Nial Friel Optimal Bayesian estimators for latent variable cluster models . . . . . . . . 1169--1186 Iker Perez and David Hodge and Theodore Kypraios Auxiliary variables for Bayesian inference in multi-class queueing networks . . . . . . . . . . . . . . . . 1187--1200 Matthew Ludkin and Idris Eckley and Peter Neal Dynamic stochastic block models: parameter estimation and detection of changes in community structure . . . . . 1201--1213 Andrew Golightly and Theodore Kypraios Efficient SMC$^2$ schemes for stochastic kinetic models . . . . . . . . . . . . . 1215--1230 Magali Champion and Victor Picheny and Matthieu Vignes Correction to: Inferring large graphs using $ \ell_1$-penalized likelihood . . 1231--1231
Eduardo García-Portugués and Michael Sòrensen and Kanti V. Mardia and Thomas Hamelryck Langevin diffusions on the torus: estimation and applications . . . . . . 1--22 Jingnan Xue and Faming Liang Double-Parallel Monte Carlo for Bayesian analysis of big data . . . . . . . . . . 23--32 Lin Su and Howard D. Bondell Best linear estimation via minimization of relative mean squared error . . . . . 33--42 Cinzia Viroli and Geoffrey J. McLachlan Deep Gaussian mixture models . . . . . . 43--51 Zhijian He and Lingjiong Zhu Asymptotic normality of extensible grid sampling . . . . . . . . . . . . . . . . 53--65 Matthew C. Edwards and Renate Meyer and Nelson Christensen Bayesian nonparametric spectral density estimation using B-spline priors . . . . 67--78 Joshua J. Bon and Kevin Murray and Berwin A. Turlach Fitting monotone polynomials in mixed effects models . . . . . . . . . . . . . 79--98 Michael Schober and Simo Särkkä and Philipp Hennig A probabilistic model for the numerical solution of initial value problems . . . 99--122 Elmar Spiegel and Thomas Kneib and Fabian Otto-Sobotka Generalized additive models with flexible response functions . . . . . . 123--138 E. del Barrio and J. A. Cuesta-Albertos and C. Matrán and A. Mayo-Íscar Robust clustering tools based on optimal transportation . . . . . . . . . . . . . 139--160 Jiaying Gu and Fei Fu and Qing Zhou Penalized estimation of directed acyclic graphs from discrete data . . . . . . . 161--176 Yi-An Ma and Emily B. Fox and Tianqi Chen and Lei Wu Irreversible samplers from jump and continuous Markov processes . . . . . . 177--202
Daiane Aparecida Zuanetti and Peter Müller and Yitan Zhu and Shengjie Yang and Yuan Ji Bayesian nonparametric clustering for large data sets . . . . . . . . . . . . 203--215 Moritz Berger and Gerhard Tutz and Matthias Schmid Tree-structured modelling of varying coefficients . . . . . . . . . . . . . . 217--229 Gersende Fort and Edouard Ollier and Adeline Samson Stochastic proximal-gradient algorithms for penalized mixed models . . . . . . . 231--253 Victor Picheny and Rémi Servien and Nathalie Villa-Vialaneix Interpretable sparse SIR for functional data . . . . . . . . . . . . . . . . . . 255--267 Dominik Müller and Claudia Czado Selection of sparse vine copulas in high dimensions with the Lasso . . . . . . . 269--287 Noboru Nomura Orthant probabilities of elliptical distributions from orthogonal projections to subspaces . . . . . . . . 289--300 Alexander Terenin and Shawfeng Dong and David Draper GPU-accelerated Gibbs sampling: a case study of the Horseshoe Probit model . . 301--310 Ruifei Cui and Perry Groot and Tom Heskes Learning causal structure from mixed data with missing values using Gaussian copula models . . . . . . . . . . . . . 311--333 Philip L. H. Yu and Hang Xu Rank aggregation using latent-scale distance-based models . . . . . . . . . 335--349 Ioulia Papageorgiou and Irini Moustaki Sampling of pairs in pairwise likelihood estimation for latent variable models with categorical observed variables . . 351--365 Xin Luo and Håkon Tjelmeland Prior specification for binary Markov mesh models . . . . . . . . . . . . . . 367--389 David P. Hofmeyr and Nicos G. Pavlidis and Idris A. Eckley Minimum spectral connectivity projection pursuit . . . . . . . . . . . . . . . . 391--414
Mohsen Maleki and Darren Wraith and Reinaldo B. Arellano-Valle Robust finite mixture modeling of multivariate unrestricted skew-normal generalized hyperbolic distributions . . 415--428 Andrew Glaws and Paul G. Constantine Gauss--Christoffel quadrature for inverse regression: applications to computer experiments . . . . . . . . . . 429--447 Florian Maire and Nial Friel and Pierre Alquier Informed sub-sampling MCMC: approximate Bayesian inference for large datasets 449--482 María Xosé Rodríguez-Álvarez and Maria Durban and Dae-Jin Lee and Paul H. C. Eilers On the estimation of variance parameters in non-standard generalised linear mixed models: application to penalised smoothing . . . . . . . . . . . . . . . 483--500 Sabrina Guastavino and Federico Benvenuto A consistent and numerically efficient variable selection method for sparse Poisson regression with applications to learning and signal recovery . . . . . . 501--516 Marina I. Knight and Matthew A. Nunes Long memory estimation for complex-valued time series . . . . . . . 517--536 Shonosuke Sugasawa and Genya Kobayashi and Yuki Kawakubo Latent mixture modeling for clustered data . . . . . . . . . . . . . . . . . . 537--548 Michael Grabchak Rejection sampling for tempered Lévy processes . . . . . . . . . . . . . . . 549--558 Antonino Abbruzzo and Ivan Vujaci\'c and Angelo M. Mineo and Ernst C. Wit Selecting the tuning parameter in penalized Gaussian graphical models . . 559--569 Junshan Shen and Hanjun Yu and Jin Yang and Chunling Liu Semiparametric Bayesian analysis for longitudinal mixed effects models with non-normal AR(1) errors . . . . . . . . 571--583 Jian Cao and Marc G. Genton and David E. Keyes and George M. Turkiyyah Hierarchical-block conditioning approximations for high-dimensional multivariate normal probabilities . . . 585--598 Jack Baker and Paul Fearnhead and Emily B. Fox and Christopher Nemeth Control variates for stochastic gradient MCMC . . . . . . . . . . . . . . . . . . 599--615
Andrew J. Black Importance sampling for partially observed temporal epidemic models . . . 617--630 Daniel W. Heck and Antony M. Overstall and Quentin F. Gronau and Eric-Jan Wagenmakers Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models . . . 631--643 Minwoo Chae and Ryan Martin and Stephen G. Walker On an algorithm for solving Fredholm integrals of the first kind . . . . . . 645--654 Andrés M. Alonso and Daniel Peña Clustering time series by linear dependency . . . . . . . . . . . . . . . 655--676 Marco Corneli and Charles Bouveyron and Pierre Latouche and Fabrice Rossi The dynamic stochastic topic block model for dynamic networks with textual edges 677--695 C. S. Gillespie and R. J. Boys Efficient construction of Bayes optimal designs for stochastic process models 697--706 Michiel Debruyne and Sebastiaan Höppner and Sven Serneels and Tim Verdonck Outlyingness: Which variables contribute most? . . . . . . . . . . . . . . . . . 707--723 Yuguang Yue and Lieven Vandenberghe and Weng Kee Wong $T$-optimal designs for multi-factor polynomial regression models via a semidefinite relaxation method . . . . . 725--738 Michael B. Giles and Takashi Goda Decision-making under uncertainty: using MLMC for efficient estimation of EVPPI 739--751 Marcelo Hartmann and Jarno Vanhatalo Laplace approximation and natural gradient for Gaussian process regression with heteroscedastic Student-$t$ model 753--773 Ajay Jasra and Kody J. H. Law and Prince Peprah Osei Multilevel particle filters for Lévy-driven stochastic differential equations . . . . . . . . . . . . . . . 775--789 Michael Fop and Thomas Brendan Murphy and Luca Scrucca Model-based clustering with sparse covariance matrices . . . . . . . . . . 791--819 Sigrunn H. Sòrbye and Eirik Myrvoll-Nilsen and Håvard Rue An approximate fractional Gaussian noise model with $ \mathcal {O}(n) $ computational cost . . . . . . . . . . . 821--833 Xi Chen and Michael Hobson and Saptarshi Das and Paul Gelderblom Improving the efficiency and robustness of nested sampling using posterior repartitioning . . . . . . . . . . . . . 835--850 Ajay Jasra and Kody J. H. Law and Prince Peprah Osei Correction to: Multilevel particle filters for Lévy-driven stochastic differential equations . . . . . . . . . 851--851
Benn Macdonald and Dirk Husmeier Model selection via marginal likelihood estimation by combining thermodynamic integration and gradient matching . . . 853--867 Javier Espinosa and Christian Hennig A constrained regression model for an ordinal response with ordinal predictors 869--890 Edward Higson and Will Handley and Michael Hobson and Anthony Lasenby Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation . . . . . . . . . . 891--913 Aleksandar A. Kolev and Gordon J. Ross Inference for ETAS models with non-Poissonian mainshock arrival times 915--931 D. Gunawan and M.-N. Tran and K. Suzuki and J. Dick and R. Kohn Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins . . . . . . . . . . . . . 933--946 Sinan Yildirim and Beyza Ermis Exact MCMC with differentially private moves . . . . . . . . . . . . . . . . . 947--963 Òyvind Langsrud Information preserving regression-based tools for statistical disclosure control 965--976 Ruifei Cui and Ioan Gabriel Bucur and Perry Groot and Tom Heskes A novel Bayesian approach for latent variable modeling from mixed data with missing values . . . . . . . . . . . . . 977--993 M. Mehdi Moradi and Ottmar Cronie and Ege Rubak and Raphael Lachieze-Rey and Jorge Mateu and Adrian Baddeley Resample-smoothing of Voronoi intensity estimators . . . . . . . . . . . . . . . 995--1010 Elizabeth Ann Maharaj and Paulo Teles and Paula Brito Clustering of interval time series . . . 1011--1034 Hiroshi Yamashita and Hideyuki Suzuki Convergence analysis of herded-Gibbs-type sampling algorithms: effects of weight sharing . . . . . . . 1035--1053 Augustin Touron Consistency of the maximum likelihood estimator in seasonal hidden Markov models . . . . . . . . . . . . . . . . . 1055--1075 Matthew Heiner and Athanasios Kottas and Stephan Munch Structured priors for sparse probability vectors with application to model selection in Markov chains . . . . . . . 1077--1093 Marco Scutari and Claudia Vitolo and Allan Tucker Learning Bayesian networks from big data with greedy search: computational complexity and efficient implementation 1095--1108 Joshua Plasse and Niall M. Adams Multiple changepoint detection in categorical data streams . . . . . . . . 1109--1125 M. Lomelí and M. Rowland and A. Gretton and Z. Ghahramani Antithetic and Monte Carlo kernel estimators for partial rankings . . . . 1127--1147 Andrew Golightly and Chris Sherlock Efficient sampling of conditioned Markov jump processes . . . . . . . . . . . . . 1149--1163 Miaoqi Li and Emily L. Kang Randomized algorithms of maximum likelihood estimation with spatial autoregressive models for large-scale networks . . . . . . . . . . . . . . . . 1165--1179
M. Girolami and I. C. F. Ipsen and C. J. Oates and A. B. Owen and T. J. Sullivan Editorial: special edition on probabilistic numerics . . . . . . . . . 1181--1183 Gene Ryan Yoo and Houman Owhadi De-noising by thresholding operator adapted wavelets . . . . . . . . . . . . 1185--1201 Martin Ehler and Manuel Gräf and Chris. J. Oates Optimal Monte Carlo integration on closed manifolds . . . . . . . . . . . . 1203--1214 R. Jagadeeswaran and Fred J. Hickernell Fast automatic Bayesian cubature using lattice sampling . . . . . . . . . . . . 1215--1229 Toni Karvonen and Simo Särkkä and Chris. J. Oates Symmetry exploits for Bayesian cubature methods . . . . . . . . . . . . . . . . 1231--1248 Simon Bartels and Jon Cockayne and Ilse C. F. Ipsen and Philipp Hennig Probabilistic linear solvers: a unifying view . . . . . . . . . . . . . . . . . . 1249--1263 Han Cheng Lie and A. M. Stuart and T. J. Sullivan Strong convergence rates of probabilistic integrators for ordinary differential equations . . . . . . . . . 1265--1283 Oksana A. Chkrebtii and David A. Campbell Adaptive step-size selection for state-space probabilistic differential equation solvers . . . . . . . . . . . . 1285--1295 Filip Tronarp and Hans Kersting and Simo Särkkä and Philipp Hennig Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective 1297--1315 Toni Karvonen and Motonobu Kanagawa and Simo Särkkä On the positivity and magnitudes of Bayesian quadrature weights . . . . . . 1317--1333 C. J. Oates and T. J. Sullivan A modern retrospective on probabilistic numerics . . . . . . . . . . . . . . . . 1335--1351
Kei Kobayashi and Henry P. Wynn Empirical geodesic graphs and CAT($k$) metrics for data analysis . . . . . . . 1--18 Zheyuan Li and Simon N. Wood Faster model matrix crossproducts for large generalized linear models with discretized covariates . . . . . . . . . 19--25 Nicholas G. Tawn and Gareth O. Roberts and Jeffrey S. Rosenthal Weight-preserving simulated tempering 27--41 Ioannis Kosmidis and Euloge Clovis Kenne Pagui and Nicola Sartori Mean and median bias reduction in generalized linear models . . . . . . . 43--59 Pierre Barbillon and Lo\"\ic Schwaller and Stéphane Robin and Andrew Flachs and Glenn Davis Stone Epidemiologic network inference . . . . 61--75 Francesco Battaglia and Domenico Cucina and Manuel Rizzo Parsimonious periodic autoregressive models for time series with evolving trend and seasonality . . . . . . . . . 77--91 Belmiro P. M. Duarte and José F. O. Granjo and Weng Kee Wong Optimal exact designs of experiments via Mixed Integer Nonlinear Programming . . 93--112 Kris Boudt and Peter J. Rousseeuw and Steven Vanduffel and Tim Verdonck The minimum regularized covariance determinant estimator . . . . . . . . . 113--128 Yafeng Cheng and Jian Qing Shi and Janet Eyre Nonlinear mixed-effects scalar-on-function models and variable selection . . . . . . . . . . . . . . . 129--140 Torsten Hothorn Transformation boosting machines . . . . 141--152 P. J. Paine and S. P. Preston and M. Tsagris and Andrew T. A. Wood Spherical regression models with general covariates and anisotropic errors . . . 153--165 Peter F. Craigmile and Debashis Mondal Estimation of long-range dependence in gappy Gaussian time series . . . . . . . 167--185 Francisco Cuevas and Denis Allard and Emilio Porcu Fast and exact simulation of Gaussian random fields defined on the sphere cross time . . . . . . . . . . . . . . . 187--194 Olivier Bock and Xavier Collilieux and François Guillamon and Emilie Lebarbier and Claire Pascal A breakpoint detection in the mean model with heterogeneous variance on fixed time intervals . . . . . . . . . . . . . 195--207
Matthew Price-Williams and Nicholas A. Heard Nonparametric self-exciting models for computer network traffic . . . . . . . . 209--220 Manuele Leonelli and Dani Gamerman Semiparametric bivariate modelling with flexible extremal dependence . . . . . . 221--236 Andrew Glaws and Paul G. Constantine and R. Dennis Cook Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experiments . . . 237--253 Luca Greco and Claudio Agostinelli Weighted likelihood mixture modeling and model-based clustering . . . . . . . . . 255--277 David Rügamer and Sonja Greven Inference for $ L_2 $-Boosting . . . . . 279--289 Sheng Ren and Emily L. Kang and Jason L. Lu MCEN: a method of simultaneous variable selection and clustering for high-dimensional multinomial regression 291--304 Ömer Deniz Akyildiz and Joaquín Míguez Nudging the particle filter . . . . . . 305--330 Gang-Hoo Kim and Sung-Ho Kim Marginal information for structure learning . . . . . . . . . . . . . . . . 331--349 Daniel Andrade and Akiko Takeda and Kenji Fukumizu Robust Bayesian model selection for variable clustering with the Gaussian graphical model . . . . . . . . . . . . 351--376 Tijana Radivojevi\'c and Elena Akhmatskaya Modified Hamiltonian Monte Carlo for Bayesian inference . . . . . . . . . . . 377--404 Aurya Javeed and Giles Hooker Timing observations of diffusions . . . 405--417 Arno Solin and Simo Särkkä Hilbert space methods for reduced-rank Gaussian process regression . . . . . . 419--446 Isadora Antoniano-Villalobos and Emanuele Borgonovo and Xuefei Lu Nonparametric estimation of probabilistic sensitivity measures . . . 447--467 Greg McSwiggan and Adrian Baddeley and Gopalan Nair Estimation of relative risk for events on a linear network . . . . . . . . . . 469--484
Panagiotis Papastamoulis Clustering multivariate data using factor analytic Bayesian mixtures with an unknown number of components . . . . 485--506 Michael B. Giles and Mateusz B. Majka and Lukasz Szpruch and Sebastian J. Vollmer and Konstantinos C. Zygalakis Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations . . . 507--524 Mohamed Reda El Amri and Céline Helbert and Olivier Lepreux and Miguel Muñoz Zuniga and Clémentine Prieur and Delphine Sinoquet Data-driven stochastic inversion via functional quantization . . . . . . . . 525--541 Ziwen An and David J. Nott and Christopher Drovandi Robust Bayesian synthetic likelihood via a semi-parametric approach . . . . . . . 543--557 Jukka Sirén and Samuel Kaski Local dimension reduction of summary statistics for likelihood-free inference 559--570 Georg Hahn Optimal allocation of Monte Carlo simulations to multiple hypothesis tests 571--586 Alvin J. K. Chua Sampling from manifold-restricted distributions using tangent bundle projections . . . . . . . . . . . . . . 587--602 Sergey Dolgov and Karim Anaya-Izquierdo and Colin Fox and Robert Scheichl Approximation and sampling of multivariate probability distributions in the tensor train decomposition . . . 603--625 Evelyn Buckwar and Massimiliano Tamborrino and Irene Tubikanec Spectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs . . . . 627--648 Achmad Choiruddin and Francisco Cuevas-Pacheco and Jean-François Coeurjolly and Rasmus Waagepetersen Regularized estimation for highly multivariate log Gaussian Cox processes 649--662 Richard G. Everitt and Richard Culliford and Felipe Medina-Aguayo and Daniel J. Wilson Sequential Monte Carlo with transformations . . . . . . . . . . . . 663--676 Eliana Christou Central quantile subspace . . . . . . . 677--695 Fan Wang and Sach Mukherjee and Sylvia Richardson and Steven M. Hill High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking . . . . . . . . . . . . . . . . 697--719 Changye Wu and Christian P. Robert Coordinate sampler: a non-reversible Gibbs-like MCMC sampler . . . . . . . . 721--730
Hien D. Nguyen and Florence Forbes and Geoffrey J. McLachlan Mini-batch learning of exponential family finite mixture models . . . . . . 731--748 Andrea Ongaro and Sonia Migliorati and Roberto Ascari A new mixture model on the simplex . . . 749--770 Peijun Sang and Jiguo Cao Functional single-index quantile regression models . . . . . . . . . . . 771--781 Eduardo F. Mendes and Christopher K. Carter and David Gunawan and Robert Kohn A flexible particle Markov chain Monte Carlo method . . . . . . . . . . . . . . 783--798 Jackie S. T. Wong and Jonathan J. Forster and Peter W. F. Smith Properties of the bridge sampler with a focus on splitting the MCMC sample . . . 799--816 Denis Dresvyanskiy and Tatiana Karaseva and Vitalii Makogin and Sergei Mitrofanov and Claudia Redenbach and Evgeny Spodarev Detecting anomalies in fibre systems using $3$-dimensional image data . . . . 817--837 Pallavi Ray and Debdeep Pati and Anirban Bhattacharya Efficient Bayesian shape-restricted function estimation with constrained Gaussian process priors . . . . . . . . 839--853 Bruno Santos and Thomas Kneib Noncrossing structured additive multiple-output Bayesian quantile regression models . . . . . . . . . . . 855--869 Keiji Takai Incomplete-data Fisher scoring method with steplength adjustment . . . . . . . 871--886 Lifeng Ye and Alexandros Beskos and Maria De Iorio and Jie Hao Monte Carlo co-ordinate ascent variational inference . . . . . . . . . 887--905 Assyr Abdulle and Giacomo Garegnani Random time step probabilistic methods for uncertainty quantification in chaotic and geometric numerical integration . . . . . . . . . . . . . . 907--932 Weichang Yu and John T. Ormerod and Michael Stewart Variational discriminant analysis with variable selection . . . . . . . . . . . 933--951 Raoul Müller and Dominic Schuhmacher and Jorge Mateu Metrics and barycenters for point pattern data . . . . . . . . . . . . . . 953--972 D. Belomestny and L. Iosipoi and E. Moulines and A. Naumov and S. Samsonov Variance reduction for Markov chains with application to MCMC . . . . . . . . 973--997 Katya Mauff and Ewout Steyerberg and Isabella Kardys and Eric Boersma and Dimitris Rizopoulos Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach . . . . . . 999--1014 Hongliang Lü and Julyan Arbel and Florence Forbes Bayesian nonparametric priors for hidden Markov random fields . . . . . . . . . . 1015--1035 Qiang Liu and Xin T. Tong Accelerating Metropolis-within-Gibbs sampler with localized computations of differential equations . . . . . . . . . 1037--1056 G. S. Rodrigues and David J. Nott and S. A. Sisson Likelihood-free approximate Gibbs sampling . . . . . . . . . . . . . . . . 1057--1073 Aijun Zhang and Hengtao Zhang and Guosheng Yin Adaptive iterative Hessian sketch via $A$-optimal subsampling . . . . . . . . 1075--1090 José L. Torrecilla and Carlos Ramos-Carreño and Manuel Sánchez-Montañés and Alberto Suárez Optimal classification of Gaussian processes in homo- and heteroscedastic settings . . . . . . . . . . . . . . . . 1091--1111
Shanika L. Wickramasuriya and Berwin A. Turlach and Rob J. Hyndman Optimal non-negative forecast reconciliation . . . . . . . . . . . . . 1167--1182 S. G. J. Senarathne and C. C. Drovandi and J. M. McGree A Laplace-based algorithm for Bayesian adaptive design . . . . . . . . . . . . 1183--1208 Haixu Wang and Jiguo Cao Estimating time-varying directed neural networks . . . . . . . . . . . . . . . . 1209--1220 Ottmar Cronie and Mehdi Moradi and Jorge Mateu Inhomogeneous higher-order summary statistics for point processes on linear networks . . . . . . . . . . . . . . . . 1221--1239 Francesco Sanna Passino and Nicholas A. Heard Classification of periodic arrivals in event time data for filtering computer network traffic . . . . . . . . . . . . 1241--1254 Linda S. L. Tan and Aishwarya Bhaskaran and David J. Nott Conditionally structured variational Gaussian approximation with importance weights . . . . . . . . . . . . . . . . 1255--1272 Luigi Augugliaro and Gianluca Sottile and Veronica Vinciotti The conditional censored graphical lasso estimator . . . . . . . . . . . . . . . 1273--1289 Francesco Sanna Passino and Nicholas A. Heard Bayesian estimation of the latent dimension and communities in stochastic blockmodels . . . . . . . . . . . . . . 1291--1307 Mirai Igarashi and Nobuhiko Terui Characterization of topic-based online communities by combining network data and user generated content . . . . . . . 1309--1324 Joonha Park and Yves Atchadé Markov chain Monte Carlo algorithms with sequential proposals . . . . . . . . . . 1325--1345 Fadhel Ayed and Marco Battiston and Federico Camerlenghi An information theoretic approach to post randomization methods under differential privacy . . . . . . . . . . 1347--1361 Luis Angel García-Escudero and Agustín Mayo-Iscar and Marco Riani Model-based clustering with determinant-and-shape constraint . . . . 1363--1380 Ajay Jasra and Fangyuan Yu and Jeremy Heng Multilevel particle filters for the non-linear filtering problem in continuous time . . . . . . . . . . . . 1381--1402 Alfredo Alegría and Xavier Emery and Christian Lantuéjoul The turning arcs: a computationally efficient algorithm to simulate isotropic vector-valued Gaussian random fields on the $d$-sphere . . . . . . . . 1403--1418 Hendrik van der Wurp and Andreas Groll and Rosalba Radice Generalised joint regression for count data: a penalty extension for competitive settings . . . . . . . . . . 1419--1432 Christian Soize and Roger G. Ghanem and Christophe Desceliers Sampling of Bayesian posteriors with a non-Gaussian probabilistic learning on manifolds from a small dataset . . . . . 1433--1457 T. Whitaker and B. Beranger and S. A. Sisson Composite likelihood methods for histogram-valued random variables . . . 1459--1477 Denis Allard and Xavier Emery and Christian Lantuéjoul Simulating space-time random fields with nonseparable Gneiting-type covariance functions . . . . . . . . . . . . . . . 1479--1495 Joonha Park and Edward L. Ionides Inference on high-dimensional implicit dynamic models using a guided intermediate resampling filter . . . . . 1497--1522 Serhat Emre Akhanli and Christian Hennig Comparing clusterings and numbers of clusters by aggregation of calibrated clustering validity indexes . . . . . . 1523--1544 Andrea Cappozzo and Francesca Greselin and Thomas Brendan Murphy Anomaly and Novelty detection for robust semi-supervised learning . . . . . . . . 1545--1571
Claes Andersson and Tomás Mrkvicka Inference for cluster point processes with over- or under-dispersed cluster sizes . . . . . . . . . . . . . . . . . 1573--1590 Antonio Lijoi and Igor Prünster and Tommaso Rigon Sampling hierarchies of discrete random structures . . . . . . . . . . . . . . . 1591--1607 Andrew Zammit-Mangion and Jonathan Rougier Multi-scale process modelling and distributed computation for spatial data 1609--1627 Aude Sportisse and Claire Boyer and Julie Josse Imputation and low-rank estimation with Missing Not At Random data . . . . . . . 1629--1643 Ömer Deniz Akyildiz and Dan Crisan and Joaquín Míguez Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization . . . . . . . . . . . . . . 1645--1663 Chiheb Ben Hammouda and Nadhir Ben Rached and Raúl Tempone Importance sampling for a robust and efficient multilevel Monte Carlo estimator for stochastic reaction networks . . . . . . . . . . . . . . . . 1665--1689 Georg Hahn and Paul Fearnhead and Idris A. Eckley BayesProject: Fast computation of a projection direction for multivariate changepoint detection . . . . . . . . . 1691--1705 Angshuman Roy and Soham Sarkar and Alok Goswami On some consistent tests of mutual independence among several random vectors of arbitrary dimensions . . . . 1707--1723 Estelle Kuhn and Catherine Matias and Tabea Rebafka Properties of the stochastic approximation EM algorithm with mini-batch sampling . . . . . . . . . . 1725--1739 David Gunawan and Khue-Dung Dang and Minh-Ngoc Tran Subsampling sequential Monte Carlo for static Bayesian models . . . . . . . . . 1741--1758 Aaron P. Lowther and Paul Fearnhead and Kjeld Jensen Semi-automated simultaneous predictor selection for regression-SARIMA models 1759--1778 Daniel Ahfock and Geoffrey J. McLachlan An apparent paradox: a classifier based on a partially classified sample may have smaller expected error rate than that if the sample were completely classified . . . . . . . . . . . . . . . 1779--1790 Hans Kersting and T. J. Sullivan and Philipp Hennig Convergence rates of Gaussian ODE filters . . . . . . . . . . . . . . . . 1791--1816
Josef Dick and Takashi Goda and Hiroya Murata Toeplitz Monte Carlo . . . . . . . . . . ?? Jian Cao and Marc G. Genton and George M. Turkiyyah Exploiting low-rank covariance structures for computing high-dimensional normal and Student-$t$ probabilities . . . . . . . . . . . . . ?? Javier Juan-Albarracín and Elies Fuster-Garcia and Juan M. García-Gómez Non-local spatially varying finite mixture models for image segmentation ?? Andrew J. Holbrook and Charles E. Loeffler and Marc A. Suchard Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data . . ?? Shengwei Hu and Yong Wang Modal Clustering Using Semiparametric Mixtures and Mode Flattening . . . . . . ?? Kitty Yuen Yi Wan and Jim E. Griffin An adaptive MCMC method for Bayesian variable selection in logistic and accelerated failure time regression models . . . . . . . . . . . . . . . . . ?? Guillaume Gautier and Rémi Bardenet and Michal Valko Fast sampling from $ \beta $-ensembles ?? Yariv Aizenbud and Boris Landa and Yoel Shkolnisky Rank-one multi-reference factor analysis ?? Zhiyan Ding and Qin Li Ensemble Kalman inversion: mean-field limit and convergence analysis . . . . . ?? Wendy K. Tam Cho and Yan Y. Liu A parallel evolutionary multiple-try Metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions . . . . . . . . . . . . . . . ?? William H. Aeberhard and Eva Cantoni and Rosalba Radice Robust fitting for generalized additive models for location, scale and shape . . ??
Ömer Deniz Akyildiz and Joaquín Míguez Convergence rates for optimised adaptive importance samplers . . . . . . . . . . ?? Marco Stefanucci and Antonio Canale Multiscale stick-breaking mixture models ?? Mark J. Meyer and Elizabeth J. Malloy and Brent A. Coull Bayesian wavelet-packet historical functional linear models . . . . . . . . ?? Rico Blaser and Piotr Fryzlewicz Regularizing axis-aligned ensembles via data rotations that favor simpler learners . . . . . . . . . . . . . . . . ?? Topi Paananen and Juho Piironen and Aki Vehtari Implicitly adaptive importance sampling ?? Gerhard Tutz and Moritz Berger Tree-structured scale effects in binary and ordinal regression . . . . . . . . . ?? Rebecca E. Wilson and Idris A. Eckley and Timothy Park A wavelet-based approach for imputation in nonstationary multivariate time series . . . . . . . . . . . . . . . . . ?? Shane Barratt and Guillermo Angeris and Stephen Boyd Optimal representative sample weighting ??
Estevão B. Prado and Rafael A. Moral and Andrew C. Parnell Bayesian additive regression trees with model trees . . . . . . . . . . . . . . ?? Ajay Jasra and Kody J. H. Law and Deng Lu Unbiased estimation of the gradient of the log-likelihood in inverse problems ?? Cinzia Viroli and Laura Anderlucci Deep mixtures of unigrams for uncovering topics in textual data . . . . . . . . . ?? Filip Tronarp and Simo Särkkä and Philipp Hennig Bayesian ODE solvers: the maximum a posteriori estimate . . . . . . . . . . ?? Santeri Karppinen and Matti Vihola Conditional particle filters with diffuse initial distributions . . . . . ?? Joseph Guinness Gaussian process learning via Fisher scoring of Vecchia's approximation . . . ?? Tom Stindl and Feng Chen Accelerating the estimation of renewal Hawkes self-exciting point processes . . ?? Christian Agrell and Kristina Rognlien Dahl Sequential Bayesian optimal experimental design for structural reliability analysis . . . . . . . . . . . . . . . . ?? Jeremie Coullon and Robert J. Webber Ensemble sampler for infinite-dimensional inverse problems ?? Valentin De Bortoli and Alain Durmus and Ana F. Vidal Efficient stochastic optimisation by unadjusted Langevin Monte Carlo . . . . ?? Gavin Ridley and Benoit Forget A simple method for rejection sampling efficiency improvement on SIMT architectures . . . . . . . . . . . . . ?? Mohammad W. Hattab and David Ruppert A mixed model approach to measurement error in semiparametric regression . . . ?? Séverine Affeldt and Lazhar Labiod and Mohamed Nadif Regularized bi-directional co-clustering ?? D. Austin Cole and Ryan B. Christianson and Robert B. Gramacy Locally induced Gaussian processes for large-scale simulation experiments . . . ?? Yiwei Wang and Jiuhai Chen and Lulu Kang Particle-based energetic variational inference . . . . . . . . . . . . . . . ?? Georg Hahn and Sharon M. Lutz and Christoph Lange A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD) . . . . . . . . . . . . . ?? Gernot Müller and Sebastian Uhl Estimation of time-varying autoregressive stochastic volatility models with stable innovations . . . . . ?? Joris Bierkens and Sebastiano Grazzi and Moritz Schauer A piecewise deterministic Monte Carlo method for diffusion bridges . . . . . . ??
Samuel M. Fischer and Mark A. Lewis A robust and efficient algorithm to find profile likelihood confidence intervals ?? Jonas Latz Analysis of stochastic gradient descent in continuous time . . . . . . . . . . . ?? Yici Chen and Ken'ichiro Tanaka Maximum likelihood estimation of the Fisher--Bingham distribution via efficient calculation of its normalizing constant . . . . . . . . . . . . . . . . ?? Diederik S. Laman Trip and Wessel N. van Wieringen A parallel algorithm for ridge-penalized estimation of the multivariate exponential family from data of mixed types . . . . . . . . . . . . . . . . . ?? Francesco Denti and Andrea Cappozzo and Francesca Greselin A two-stage Bayesian semiparametric model for novelty detection with robust prior information . . . . . . . . . . . ?? Xiong Lyu and Mickaël Binois and Michael Ludkovski Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation . . . . . . . . . . . . . ?? Nicolas Jouvin and Charles Bouveyron and Pierre Latouche A Bayesian Fisher--EM algorithm for discriminative Gaussian subspace clustering . . . . . . . . . . . . . . . ?? Belmiro P. M. Duarte and Anthony C. Atkinson and Nuno M. C. Oliveira Optimal experimental design for linear time invariant state-space models . . . ?? Feng Zhou and Simon Luo and Zhidong Li and Xuhui Fan and Yang Wang and Arcot Sowmya and Fang Chen Efficient EM-variational inference for nonparametric Hawkes process . . . . . . ?? Augusto Fasano and Giovanni Rebaudo and Daniele Durante and Sonia Petrone A closed-form filter for binary time series . . . . . . . . . . . . . . . . . ?? G. Fort and P. Gach and E. Moulines Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence ?? Vojtech Kejzlar and Mookyong Son and Shrijita Bhattacharya and Tapabrata Maiti A fast and calibrated computer model emulator: an empirical Bayes approach ?? Rémi Leluc and François Portier and Johan Segers Control variate selection for Monte Carlo integration . . . . . . . . . . . ?? Duncan Lee and Kitty Meeks and William Pettersson Improved inference for areal unit count data using graph-based optimisation . . ??
Linna Wang and Yichen Qin and Yang Li Confidence graphs for graphical model selection . . . . . . . . . . . . . . . ?? Thomas Maullin-Sapey and Thomas E. Nichols Fisher Scoring for crossed factor linear mixed models . . . . . . . . . . . . . . ?? Satya Prakash Singh and Siuli Mukhopadhyay and Harsh Raj Min-max crossover designs for two treatments binary and Poisson crossover trials . . . . . . . . . . . . . . . . . ?? Junyang Wang and Jon Cockayne and T. J. Sullivan and Chris. J. Oates Bayesian numerical methods for nonlinear partial differential equations . . . . . ?? Vladimir Fanaskov Uncertainty calibration for probabilistic projection methods . . . . ?? Yu Luo and David A. Stephens Bayesian inference for continuous-time hidden Markov models with an unknown number of states . . . . . . . . . . . . ?? Daniel Ahfock and Saumyadipta Pyne and Geoffrey J. McLachlan Data fusion using factor analysis and low-rank matrix completion . . . . . . . ?? Jeremie Houssineau and Jiajie Zeng and Ajay Jasra Uncertainty modelling and computational aspects of data association . . . . . . ?? D. I. Palade and M. Vlad Fast generation of Gaussian random fields for direct numerical simulations of stochastic transport . . . . . . . . ?? Minas Karamanis and Florian Beutler Ensemble slice sampling . . . . . . . . ?? Joshua J. Bon and Anthony Lee and Christopher Drovandi Accelerating sequential Monte Carlo with surrogate likelihoods . . . . . . . . . ?? Fadhel Ayed and François Caron Nonnegative Bayesian nonparametric factor models with completely random measures . . . . . . . . . . . . . . . . ?? Renzo Caballero and Ahmed Kebaier and Marco Scavino and Raúl Tempone Quantifying uncertainty with a derivative tracking SDE model and application to wind power forecast data ?? Selin Damla Ahipasaoglu A branch-and-bound algorithm for the exact optimal experimental design problem . . . . . . . . . . . . . . . . ?? Joachim Schreurs and Iwein Vranckx and Johan A. K. Suykens and Peter J. Rousseeuw Outlier detection in non-elliptical data by kernel MRCD . . . . . . . . . . . . . ?? Jonas Latz and Juan P. Madrigal-Cianci and Fabio Nobile and Raúl Tempone Generalized parallel tempering on Bayesian inverse problems . . . . . . . ?? Jacob Vorstrup Goldman and Sumeetpal S. Singh Spatiotemporal blocking of the bouncy particle sampler for efficient inference in state-space models . . . . . . . . . ??
Nadhir Ben Rached and Abdul-Lateef Haji-Ali and Raúl Tempone Efficient importance sampling for large sums of independent and identically distributed random variables . . . . . . ?? Xuan Dang and Shuai Huang and Xiaoning Qian Penalized Cox's proportional hazards model for high-dimensional survival data with grouped predictors . . . . . . . . ?? Alix Marie d'Avigneau and Sumeetpal S. Singh and Lawrence M. Murray Anytime parallel tempering . . . . . . . ?? Víctor Elvira and Joaquín Miguez and Petar M. Djuri\'c On the performance of particle filters with adaptive number of particles . . . ?? Radoslav Harman and Lenka Filová and Samuel Rosa Optimal design of multifactor experiments via grid exploration . . . . ?? Giles Hooker and Lucas Mentch and Siyu Zhou Unrestricted permutation forces extrapolation: variable importance requires at least one more model, or there is no free variable importance . . ?? Chaofan Huang and V. Roshan Joseph and Douglas M. Ray Constrained minimum energy designs . . . ?? Alec Koppel and Hrusikesha Pradhan and Ketan Rajawat Consistent online Gaussian process regression without the sample complexity bottleneck . . . . . . . . . . . . . . . ?? Jeong Eun Lee and Geoff K. Nicholls Tree based credible set estimation . . . ?? Yinan Mao and Xueou Wang and Michael Evans Detecting conflicting summary statistics in likelihood-free inference . . . . . . ?? John Moriarty and Jure Vogrinc and Alessandro Zocca A Metropolis-class sampler for targets with non-convex support . . . . . . . . ?? Kimmo Suotsalo and Yingying Xu and Johan Pensar High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood . . . . . . . . . . . ?? Minh-Ngoc Tran and Dang H. Nguyen and Duy Nguyen Variational Bayes on manifolds . . . . . ?? Zheng Zhao and Muhammad Emzir and Simo Särkkä Deep state-space Gaussian processes . . ??
Umberto Amato and Anestis Antoniadis and Ir\`ene Gijbels Wavelet-based robust estimation and variable selection in nonparametric additive models . . . . . . . . . . . . ?? D. Belomestny and E. Moulines and S. Samsonov Variance reduction for additive functionals of Markov chains via martingale representations . . . . . . . ?? Gabriel Boisvert-Beaudry and Myl\`ene Bédard MALA with annealed proposals: a generalization of locally and globally balanced proposal distributions . . . . ?? Francesco Denti and Andrea Cappozzo and Francesca Greselin Correction to: A two-stage Bayesian semiparametricmodel for novelty detection with robust prior information ?? Christophe Dutang and Quentin Guibert An explicit split point procedure in model-based trees allowing for a quick fitting of GLM trees and GLM forests . . ?? Gabriel Frisch and Jean-Benoist Leger and Yves Grandvalet Learning from missing data with the binary latent block model . . . . . . . ?? Luis A. García-Escudero and Agustín Mayo-Iscar and Marco Riani Constrained parsimonious model-based clustering . . . . . . . . . . . . . . . ?? Simon Godsill and Yaman Kindap Point process simulation of generalised inverse Gaussian processes and estimation of the Jaeger integral . . . ?? Andrew Golightly and Chris Sherlock Augmented pseudo-marginal Metropolis--Hastings for partially observed diffusion processes . . . . . . ?? Flávio B. Gonçalves and Lívia M. Dutra and Roger W. C. Silva Exact and computationally efficient Bayesian inference for generalized Markov modulated Poisson processes . . . ?? Yaofang Hu and Wanjie Wang and Yi Yu Graph matching beyond perfectly-overlapping Erd\Hos--Rényi random graphs . . . . . . . . . . . . . ?? Corinne Jones and Vincent Roulet and Zaid Harchaoui Discriminative clustering with representation learning with any ratio of labeled to unlabeled data . . . . . . ?? Marcin Jurek and Matthias Katzfuss Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering . . . . . . . . . . . . . . . ?? Hyotae Kim and Athanasios Kottas Erlang mixture modeling for Poisson process intensities . . . . . . . . . . ?? Juan Kuntz and Francesca R. Crucinio and Adam M. Johansen Product-form estimators: exploiting independence to scale up Monte Carlo . . ?? Marc Lambert and Silv\`ere Bonnabel and Francis Bach The recursive variational Gaussian approximation (R-VGA) . . . . . . . . . ?? Yang Liu and Robert J. B. Goudie Stochastic approximation cut algorithm for inference in modularized Bayesian models . . . . . . . . . . . . . . . . . ?? L. Mihaela Paun and Dirk Husmeier Emulation-accelerated Hamiltonian Monte Carlo algorithms for parameter estimation and uncertainty quantification in differential equation models . . . . . . . . . . . . . . . . . ?? Lena Sembach and Jan Pablo Burgard and Volker Schulz A Riemannian Newton trust-region method for fitting Gaussian mixture models . . ?? Nathaniel Tomasetti and Catherine Forbes and Anastasios Panagiotelis Updating Variational Bayes: fast sequential posterior inference . . . . . ?? Jiangqi Wu and Linjie Wen and Simon Maskell Ensemble Kalman filter based sequential Monte Carlo sampler for sequential Bayesian inference . . . . . . . . . . . ??
Assyr Abdulle and Grigorios A. Pavliotis and Andrea Zanoni Eigenfunction martingale estimating functions and filtered data for drift estimation of discretely observed multiscale diffusions . . . . . . . . . ?? Martin Eigel and Robert Gruhlke and Manuel Marschall Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion . . . . . . . . . ?? Tianyu Guan and Zhenhua Lin and Jiguo Cao Sparse functional partial least squares regression with a locally sparse slope function . . . . . . . . . . . . . . . . ?? Markus Hainy and David J. Price and Christopher Drovandi Optimal Bayesian design for model discrimination via classification . . . ?? Benoit Kugler and Florence Forbes and Sylvain Douté Fast Bayesian inversion for high dimensional inverse problems . . . . . . ?? Andrew A. Manderson and Robert J. B. Goudie A numerically stable algorithm for integrating Bayesian models using Markov melding . . . . . . . . . . . . . . . . ?? Christian Molkenthin and Christian Donner and Manfred Opper GP-ETAS: semiparametric Bayesian inference for the spatio-temporal epidemic type aftershock sequence model ?? Panagiotis Papastamoulis and Ioannis Ntzoufras On the identifiability of Bayesian factor analytic models . . . . . . . . . ?? Francesco Sanna Passino and Nicholas A. Heard Latent structure blockmodels for Bayesian spectral graph clustering . . . ?? Teemu Säilynoja and Paul-Christian Bürkner and Aki Vehtari Graphical test for discrete uniformity and its applications in goodness-of-fit evaluation and multiple sample comparison . . . . . . . . . . . . . . . ?? Sebastian M. Schmon and Philippe Gagnon Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics . . . . . . . . ?? Jarkko Suuronen and Neil K. Chada and Lassi Roininen Cauchy Markov random field priors for Bayesian inversion . . . . . . . . . . . ?? Michalis K. Titsias and Jakub Sygnowski and Yutian Chen Sequential changepoint detection in neural networks with checkpoints . . . . ??
Themistoklis Botsas and Lachlan R. Mason and Indranil Pan Rule-based Bayesian regression . . . . . ?? Antonio Canale and Riccardo Corradin and Bernardo Nipoti Importance conditional sampling for Pitman-Yor mixtures . . . . . . . . . . ?? Christopher Drovandi and David T. Frazier A comparison of likelihood-free methods with and without summary statistics . . ?? Giles Hooker and Han Lin Shang Selecting the derivative of a functional covariate in scalar-on-function regression . . . . . . . . . . . . . . . ?? John Hughes Sklar's Omega: a Gaussian copula-based framework for assessing agreement . . . ?? Nick James and Max Menzies Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes . . . . . . . . ?? Lucas Kook and Beate Sick and Peter Bühlmann Distributional anchor regression . . . . ?? Jianfeng Lu and Lihan Wang Complexity of zigzag sampling algorithm for strongly log-concave distributions ?? Giulia Marchello and Audrey Fresse and Charles Bouveyron Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance . . . . ?? Hamza Ruzayqat and Neil K. Chada and Ajay Jasra Multilevel estimation of normalization constants using ensemble Kalman--Bucy filters . . . . . . . . . . . . . . . . ?? Srijata Samanta and Kshitij Khare and George Michailidis A generalized likelihood-based Bayesian approach for scalable joint regression and covariance selection in high dimensions . . . . . . . . . . . . . . . ?? Denishrouf Thesingarajah and Adam M. Johansen The node-wise Pseudo-marginal method: model selection with spatial dependence on latent graphs . . . . . . . . . . . . ?? Willem van den Boom and Ajay Jasra and Johan G. Eriksson Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo . . . . . . . . . . . . . . . . . ?? Yan Zhong and Jianhua Z. Huang Biclustering via structured regularized matrix decomposition . . . . . . . . . . ??
Marina Meila and Annelise Wagner and Christopher Meek Recursive inversion models for permutations . . . . . . . . . . . . . . ?? Alexander T. M. Fisch and Lawrence Bardwell and Idris A. Eckley Real time anomaly detection and categorisation . . . . . . . . . . . . . ?? Vasyl Hafych and Philipp Eller and Oliver Schulz and Allen Caldwel Parallelizing MCMC sampling via space partitioning . . . . . . . . . . . . . . ?? Jingnan Zhang and Junhui Wang Identifiability and parameter estimation of the overlapped stochastic co-block model . . . . . . . . . . . . . . . . . ?? Wei Deng and Guang Lin and Faming Liang An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization . . . ?? Haoxin Zhuang and Liqun Diao and Grace Yi Polya tree-based nearest neighborhood regression . . . . . . . . . . . . . . . ?? Andrew D. Davis and Youssef Marzouk and Aaron Smith and Natesh Pillai Rate-optimal refinement strategies for local approximation MCMC . . . . . . . . ?? Luca Merlo and Antonello Maruotti and Lea Petrella and Antonio Punzo Quantile hidden semi-Markov models for multivariate time series . . . . . . . . ?? Mabel Morales-Otero and Virgilio Gómez-Rubio and Vicente Núñez-Antón Fitting double hierarchical models with the integrated nested Laplace approximation . . . . . . . . . . . . . ?? Zuheng Xu and Trevor Campbell The computational asymptotics of Gaussian variational inference and the Laplace approximation . . . . . . . . . ?? Stéphane Girard and Gilles Stupfler and Antoine Usseglio-Carleve On automatic bias reduction for extreme expectile estimation . . . . . . . . . . ?? Daniel Paulin and Ajay Jasra and Alexandros Beskos and Dan Crisan A 4D-Var method with flow-dependent background covariances for the shallow-water equations . . . . . . . . ??
Baris Alparslan and Sinan Yildirim Statistic selection and MCMC for differentially private Bayesian estimation . . . . . . . . . . . . . . . ?? Frank Rotiroti and Stephen G. Walker Computing marginal likelihoods via the Fourier integral theorem and pointwise estimation of posterior densities . . . ?? Alex Sharp and Ryan Browne A joint latent factor analyzer and functional subspace model for clustering multivariate functional data . . . . . . ?? Nan Zhang and Muye Nanshan and Jiguo Cao A Joint estimation approach to sparse additive ordinary differential equations ?? Lucas Kock and Nadja Klein and David J. Nott Variational inference and sparsity in high-dimensional deep Gaussian mixture models . . . . . . . . . . . . . . . . . ?? Sabrina Sixta and Jeffrey S. Rosenthal Convergence rate bounds for iterative random functions using one-shot coupling ?? Hanwen Xing Improving bridge estimators via $f$-GAN ?? Isa Marques and Thomas Kneib and Nadja Klein A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes . . . . . ?? Suman Majumder and Yawen Guan and Brian J. Reich and Arvind K. Saibaba Kryging: geostatistical analysis of large-scale datasets using Krylov subspace methods . . . . . . . . . . . . ?? Ben Sherwood and Shaobo Li Quantile regression feature selection and estimation with grouped variables using Huber approximation . . . . . . . ?? Cunjie Lin and Nan Qiao and Wenli Zhang and Yang Li and Shuangge Ma Default risk prediction and feature extraction using a penalized deep neural network . . . . . . . . . . . . . . . . ?? Marco Scutari and Francesca Panero and Manuel Proissl Achieving fairness with a simple ridge penalty . . . . . . . . . . . . . . . . ?? Benjamin J. Zhang and Youssef M. Marzouk and Konstantinos Spiliopoulos Geometry-informed irreversible perturbations for accelerated convergence of Langevin dynamics . . . . ?? Alexandre Constantin and Mathieu Fauvel and Stéphane Girard Mixture of multivariate Gaussian processes for classification of irregularly sampled satellite image time-series . . . . . . . . . . . . . . ?? Jimmy Olsson and Tatjana Pavlenko and Felix L. Rios Sequential sampling of junction trees for decomposable graphs . . . . . . . . ?? Piergiacomo Sabino Exact simulation of normal tempered stable processes of OU type with applications . . . . . . . . . . . . . . ?? Yiolanda Englezou and Timothy W. Waite and David C. Woods Approximate Laplace importance sampling for the estimation of expected Shannon information gain in high-dimensional Bayesian design for nonlinear models . . ?? Jérôme-Alexis Chevalier and Tuan-Binh Nguyen and Bertrand Thirion and Joseph Salmon Spatially relaxed inference on high-dimensional linear models . . . . . ?? Xitong Liang and Samuel Livingstone and Jim Griffin Adaptive random neighbourhood informed Markov chain Monte Carlo for high-dimensional Bayesian variable selection . . . . . . . . . . . . . . . ?? Florence Forbes and Hien Duy Nguyen and TrungTin Nguyen and Julyan Arbel Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors . . ?? Fernando Casas and Jesús María Sanz-Serna and Luke Shaw Split Hamiltonian Monte Carlo revisited ?? Xiaohao Cai and Jason D. McEwen and Marcelo Pereyra Proximal nested sampling for high-dimensional Bayesian model selection . . . . . . . . . . . . . . . ?? Theodore Papamarkou and Farzana Nasrin and Austin Lawson and Na Gong and Orlando Rios and Vasileios Maroulas A random persistence diagram generator ?? Alex Stringer Automatic differentiation of Box--Cox transformations with application to random effects models for continuous non-normal response . . . . . . . . . . ?? Andrea Bucci and Luigi Ippoliti and Pasquale Valentini Comparing unconstrained parametrization methods for return covariance matrix prediction . . . . . . . . . . . . . . . ?? Tiandong Wang and Jun Yan and Yelie Yuan and Panpan Zhang Generating directed networks with predetermined assortativity measures . . ?? Belmiro P. M. Duarte and Anthony C. Atkinson and Nuno M. C. Oliveira Optimal designs for dose-escalation trials and individual allocations in cohorts . . . . . . . . . . . . . . . . ?? Chew-Seng Chee and Byungtae Seo Density deconvolution under a $k$-monotonicity constraint . . . . . . ?? Philip Greengard and Michael O'Neil Efficient reduced-rank methods for Gaussian processes with eigenfunction expansions . . . . . . . . . . . . . . . ??
Yannis G. Yatracos Limitations of the Wasserstein MDE for univariate data . . . . . . . . . . . . ?? Swapnil Mishra and Seth Flaxman and Tresnia Berah and Harrison Zhu and Mikko Pakkanen and Samir Bhatt $ \pi $ VAE: a stochastic process prior for Bayesian deep learning with MCMC . . ?? Linjie Wen and Jinglai Li Affine-mapping based variational ensemble Kalman filter . . . . . . . . . ?? Leigh Shlomovich and Edward A. K. Cohen and Niall Adams A parameter estimation method for multivariate binned Hawkes processes . . ?? Xiaoyu Ma and Sylvain Sardy and Nick Hengartner and Nikolai Bobenko and Yen Ting Lin A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks . . . . . . . ?? Elena Castilla and Mar\'ìa Jaenada and Nirian Mart\'ìn and Leandro Pardo Robust approach for comparing two dependent normal populations through Wald-type tests based on Rényi's pseudodistance estimators . . . . . . . ?? Michael C. Rendleman and Brian J. Smith and Guadalupe Canahuate and Terry A. Braun and John M. Buatti and Thomas L. Casavant Representative random sampling: an empirical evaluation of a novel bin stratification method for model performance estimation . . . . . . . . . ?? Jochen Bröcker Uniform calibration tests for forecasting systems with small lead time ?? Tobias Ròikjer and Asger Hobolth and Kasper Munch Graph-based algorithms for phase-type distributions . . . . . . . . . . . . . ?? Fabrizio Laurini and Paul Fearnhead and Jonathan Tawn Limit theory and robust evaluation methods for the extremal properties of $ {\rm GARCH}(p, q) $ processes . . . . . ?? Chunshan Liu and Daniel R. Kowal and Marina Vannucci Dynamic and robust Bayesian graphical models . . . . . . . . . . . . . . . . . ?? Shiyuan He and Hanxuan Ye and Kejun He Spline estimation of functional principal components via manifold conjugate gradient algorithm . . . . . . ?? Alice Corbella and Simon E. F. Spencer and Gareth O. Roberts Automatic zig-zag sampling in practice ?? Siavash Ameli and Shawn C. Shadden Interpolating log-determinant and trace of the powers of matrix \boldmath $ A + t B $ . . . . . . . . . . . . . . . . . ?? Eric D. Schoen and Pieter T. Eendebak and Alan R. Vazquez and Peter Goos Systematic enumeration of definitive screening designs . . . . . . . . . . . ?? Karl L. Hallgren and Nicholas A. Heard and Niall M. Adams Changepoint detection in non-exchangeable data . . . . . . . . . ??
Zheyuan Li and Jiguo Cao Automatic search intervals for the smoothing parameter in penalized splines ?? Rico Krueger and Michel Bierlaire and Thomas Gasos and Prateek Bansal Robust discrete choice models with t-distributed kernel errors . . . . . . ?? Francisco Vargas and Andrius Ovsianas and David Fernandes and Mark Girolami and Neil D. Lawrence and Nikolas Nüsken Bayesian learning via neural Schrödinger--Föllmer flows . . . . . . . . ?? Michael Grabchak and Piergiacomo Sabino Efficient simulation of $p$-tempered $ \alpha $-stable OU processes . . . . . . ?? Marco Capó and Aritz Pérez and José A. Lozano LASSO for streaming data with adaptative filtering . . . . . . . . . . . . . . . ?? Angelos Alexopoulos and Petros Dellaportas and Michalis K. Titsias Variance reduction for Metropolis--Hastings samplers . . . . . ?? Alan R. Vazquez and Weng Kee Wong and Peter Goos Constructing two-level $ Q_B $-optimal screening designs using mixed-integer programming and heuristic algorithms . . ?? Joris Bierkens and Sebastiano Grazzi and Frank van der Meulen and Moritz Schauer Sticky PDMP samplers for sparse and local inference problems . . . . . . . . ?? Si-Yu Yi and Yong-Dao Zhou Model-free global likelihood subsampling for massive data . . . . . . . . . . . . ?? Nha Vo-Thanh and Hans-Peter Piepho Bayesian $A$-optimal two-phase designs with a single blocking factor in each phase . . . . . . . . . . . . . . . . . ?? Anna L. Smith and Tian Zheng and Andrew Gelman Prediction scoring of data-driven discoveries for reproducible research ?? Zhirong Yang and Yuwei Chen and Denis Sedov and Samuel Kaski and Jukka Corander Stochastic cluster embedding . . . . . . ?? Shufei Ge and Shijia Wang and Lloyd Elliott Shape modeling with spline partitions ?? Luc Pronzato Performance analysis of greedy algorithms for minimising a Maximum Mean Discrepancy . . . . . . . . . . . . . . ?? Rou Zhong and Shishi Liu and Haocheng Li and Jingxiao Zhang Sparse logistic functional principal component analysis for binary data . . . ?? Lukas Cironis and Jan Palczewski and Georgios Aivaliotis Automatic model training under restrictive time constraints . . . . . . ?? Gabriel Riutort-Mayol and Paul-Christian Bürkner and Michael R. Andersen and Arno Solin and Aki Vehtari Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming . . . . . . . ?? Vojtech Kejzlar and Tapabrata Maiti Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration . . . . . . . ?? Mohamed Maama and Ajay Jasra and Hernando Ombao Bayesian parameter inference for partially observed stochastic differential equations driven by fractional Brownian motion . . . . . . . ?? Nikolai Spuck and Matthias Schmid and Nils Heim and Ute Klarmann-Schulz and Achim Hörauf and Moritz Berger Flexible tree-structured regression models for discrete event times . . . . ?? Victor Freguglia and Nancy L. Garcia Detecting renewal states in chains of variable length via intrinsic Bayes factors . . . . . . . . . . . . . . . . ?? Andrew M. Raim Direct sampling with a step function . . ?? Kamran Pentland and Massimiliano Tamborrino and T. J. Sullivan and James Buchanan and L. C. Appel GParareal: a time-parallel ODE solver using Gaussian process emulation . . . . ?? Lucas Kock and Nadja Klein and David J. Nott Correction to: Variational inference and sparsity in high-dimensional deep Gaussian mixture models . . . . . . . . ?? Lisa Gaedke-Merzhäuser and Janet van Niekerk and Olaf Schenk and Håvard Rue Parallelized integrated nested Laplace approximations for fast Bayesian inference . . . . . . . . . . . . . . . ?? Pekka Korhonen and Francis K. C. Hui and Jenni Niku and Sara Taskinen Fast and universal estimation of latent variable models using extended variational approximations . . . . . . . ?? Yeonjoo Lee and Natalia Rojas-Perilla and Marina Runge and Timo Schmid Variable selection using conditional AIC for linear mixed models with data-driven transformations . . . . . . . . . . . . ?? Thomas Rusch and Patrick Mair and Kurt Hornik Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling . . . . . . . . ?? Arnaud Poinas and Rémi Bardenet On proportional volume sampling for experimental design in general spaces ?? Junyi Zhang and Angelos Dassios Truncated Poisson--Dirichlet approximation for Dirichlet process hierarchical models . . . . . . . . . . ?? Hiroshi Yamashita and Hideyuki Suzuki and Kazuyuki Aihara Entropic herding . . . . . . . . . . . . ?? Katherine A. L. Valeriano and Christian E. Galarza and Larissa A. Matos Moments and random number generation for the truncated elliptical family of distributions . . . . . . . . . . . . . ?? Atlanta Chakraborty and David J. Nott and Christopher C. Drovandi and David T. Frazier and Scott A. Sisson Modularized Bayesian analyses and cutting feedback in likelihood-free inference . . . . . . . . . . . . . . . ?? Daniel Ahfock and William J. Astle and Sylvia Richardson On randomized sketching algorithms and the Tracy--Widom law . . . . . . . . . . ?? Bradley Wakefield and Yan-Xia Lin and Rathin Sarathy and Krishnamurty Muralidhar Moment-based density estimation of confidential micro-data: a computational statistics approach . . . . . . . . . . ??
Belén Pulido and Alba M. Franco-Pereira and Rosa E. Lillo A fast epigraph and hypograph-based approach for clustering functional data ?? David Rügamer and Philipp F. M. Baumann and Thomas Kneib and Torsten Hothorn Probabilistic time series forecasts with autoregressive transformation models . . ?? Li-Pang Chen De-noising boosting methods for variable selection and estimation subject to error-prone variables . . . . . . . . . ?? Shouto Yonekura and Shonosuke Sugasawa Adaptation of the tuning parameter in general Bayesian inference with robust divergence . . . . . . . . . . . . . . . ?? Eya Ben Amar and Nadhir Ben Rached and Abdul-Lateef Haji-Ali and Raúl Tempone State-dependent importance sampling for estimating expectations of functionals of sums of independent random variables ?? Clément Duhamel and Céline Helbert and Miguel Munoz Zuniga and Clémentine Prieur and Delphine Sinoquet A SUR version of the Bichon criterion for excursion set estimation . . . . . . ?? Marko Järvenpää and Jukka Corander On predictive inference for intractable models via approximate Bayesian computation . . . . . . . . . . . . . . ?? Huibin Weng and Olivier Parent Beyond homophilic dyadic interactions: the impact of network formation on individual outcomes . . . . . . . . . . ?? Ionut Paun and Dirk Husmeier and Colin J. Torney Stochastic variational inference for scalable non-stationary Gaussian process regression . . . . . . . . . . . . . . . ?? Zhuang Yang and Li Ma Adaptive step size rules for stochastic optimization in large-scale learning . . ?? Gery Geenens and Alicia Nieto-Reyes and Giacomo Francisci Statistical depth in abstract metric spaces . . . . . . . . . . . . . . . . . ?? Ensiyeh Nezakati and Eugen Pircalabelu Unbalanced distributed estimation and inference for the precision matrix in Gaussian graphical models . . . . . . . ?? Christopher J. Geoga and Oana Marin and Michel Schanen and Michael L. Stein Fitting Matérn smoothness parameters using automatic differentiation . . . . ?? Mateusz B. Majka and Marc Sabate-Vidales and Lukasz Szpruch Multi-index antithetic stochastic gradient algorithm . . . . . . . . . . . ?? Iván Gutiérrez and Luis Gutiérrez and Danilo Alvares A new flexible Bayesian hypothesis test for multivariate data . . . . . . . . . ?? João Victor B. de Freitas and Caio L. N. Azevedo and Juvêncio S. Nobre A stochastic approximation ECME algorithm to semi-parametric scale mixtures of centred skew normal regression models . . . . . . . . . . . ?? Al-Fahad Al-Qadhi and Carey E. Priebe and Hayden S. Helm and Vince Lyzinski Subgraph nomination: query by example subgraph retrieval in networks . . . . . ?? Philipp Sterzinger and Ioannis Kosmidis Maximum softly-penalized likelihood for mixed effects logistic regression . . . ?? Zaida C. Quiroz and Marcos O. Prates and Dipak K. Dey and H.åvard Rue Fast Bayesian inference of block Nearest Neighbor Gaussian models for large data ?? Edoardo Redivo and Cinzia Viroli and Alessio Farcomeni Quantile-distribution functions and their use for classification, with application to na\"\ive Bayes classifiers . . . . . . . . . . . . . . ??
Myeongjong Kang and Matthias Katzfuss Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference . . . . . . . ?? Xiaoxiao Zhou and Xinyuan Song Functional concurrent hidden Markov model . . . . . . . . . . . . . . . . . ?? Chiheb Ben Hammouda and Nadhir Ben Rached and Raúl Tempone and Sophia Wiechert Learning-based importance sampling via stochastic optimal control for stochastic reaction networks . . . . . . ?? Chien-Yu Peng and Yi-Shian Dong and Tsai-Hung Fan The first-passage-time moments for the Hougaard process and its Birnbaum--Saunders approximation . . . . ?? Filippo Antonazzo and Christophe Biernacki and Christine Keribin Frugal Gaussian clustering of huge imbalanced datasets through a bin-marginal approach . . . . . . . . . ?? Diala Hawat and Guillaume Gautier and Rémi Bardenet and Raphaël Lachi\`eze-Rey On estimating the structure factor of a point process, with applications to hyperuniformity . . . . . . . . . . . . ?? Xin Liang On the optimality of the Oja's algorithm for online PCA . . . . . . . . . . . . . ?? Håkon Gryvill and Håkon Tjelmeland A sparse matrix formulation of model-based ensemble Kalman filter . . . ?? Marno Basson and Tobias M. Louw and Theresa R. Smith Variational Tobit Gaussian Process Regression . . . . . . . . . . . . . . . ?? Gersende Fort and Eric Moulines Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization . . . ?? Jeremie Coullon and Leah South and Christopher Nemeth Efficient and generalizable tuning strategies for stochastic gradient MCMC ?? Min Xu and Zhongfeng Qin A Bayesian parametrized method for interval-valued regression models . . . ?? Maolin Pan and Minggao Gu and Xianyi Wu and Xiaodan Fan Globally and symmetrically identified Bayesian multinomial probit model . . . ?? Enes Makalic and Daniel F. Schmidt Maximum likelihood estimation of the Weibull distribution with reduced bias ?? Marc Lambert and Silv\`ere Bonnabel and Francis Bach The limited-memory recursive variational Gaussian approximation (L-RVGA) . . . . ?? Meadhbh O'Neill and Kevin Burke Variable selection using a smooth information criterion for distributional regression models . . . . . . . . . . . ?? Yujia Ding and Qidi Peng and Zhengming Song and Hansen Chen Variable selection and regularization via arbitrary rectangle-range generalized elastic net . . . . . . . . ?? Kangning Wang and Shaomin Li Distributed statistical optimization for non-randomly stored big data with application to penalized learning . . . ?? Yiming Liu and Shaochen Wang and Wang Zhou General Jackknife empirical likelihood and its applications . . . . . . . . . . ??
Ilsuk Kang and Hosik Choi and Young Joo Yoon and Junyoung Park and Soon-Sun Kwon and Cheolwoo Park Fréchet distance-based cluster analysis for multi-dimensional functional data ?? Vaidehi Dixit and Ryan Martin A PRticle filter algorithm for nonparametric estimation of multivariate mixing distributions . . . . . . . . . . ?? Alessandro Mastrototaro and Jimmy Olsson Adaptive online variance estimation in particle filters: the ALVar estimator ?? Chen Huang and Jieli Ding and Yanqin Feng A quadratic upper bound algorithm for regression analysis of credit risk under the proportional hazards model with case-cohort data . . . . . . . . . . . . ?? Xiaodong Yang and Jun S. Liu Convergence rate of multiple-try Metropolis independent sampler . . . . . ?? Ben Bettisworth and Alexander I. Jordan and Alexandros Stamatakis Phylourny: efficiently calculating elimination tournament win probabilities via phylogenetic methods . . . . . . . . ?? Pete Philipson and Alan Huang A fast look-up method for Bayesian mean-parameterised Conway--Maxwell--Poisson regression models . . . . . . . . . . . . . . . . . ?? Imke Botha and Robert Kohn and Leah South and Christopher Drovandi Automatically adapting the number of state particles in SMC$^2$ . . . . . . . ?? Tianfang Zhang and Rasmus Bokrantz and Jimmy Olsson A similarity-based Bayesian mixture-of-experts model . . . . . . . . ?? Paul G. Beckman and Christopher J. Geoga and Michael L. Stein and Mihai Anitescu Scalable computations for nonstationary Gaussian processes . . . . . . . . . . . ?? Armin Eftekhari and Luis Vargas and Konstantinos C. Zygalakis The forward-backward envelope for sampling with the overdamped Langevin algorithm . . . . . . . . . . . . . . . ?? Haixiang Zhang and Xin Li A framework for mediation analysis with massive data . . . . . . . . . . . . . . ?? Efstratios Palias and Ata Kabán The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification . . . . . . ?? Zishu Zhan and Xiangjie Li and Jingxiao Zhang Partial replacement imputation estimation for partially linear models with complex missing pattern covariates ?? Shiwei Lan and Shuyi Li and Mirjeta Pasha Bayesian spatiotemporal modeling for inverse problems . . . . . . . . . . . . ?? Sijing Li and Cheng Zhang and Zhiwen Zhang and Hongkai Zhao A data-driven and model-based accelerated Hamiltonian Monte Carlo method for Bayesian elliptic inverse problems . . . . . . . . . . . . . . . . ?? Anna Bonnet and Miguel Martinez Herrera and Maxime Sangnier Inference of multivariate exponential Hawkes processes with inhibition and application to neuronal activity . . . . ??
Walter R. Gilks and Lukas Cironis and Stuart Barber Wavelet Monte Carlo: a principle for sampling from complex distributions . . ?? Robin Richter and Shankar Bhamidi and Sach Mukherjee Improved baselines for causal structure learning on interventional data . . . . ?? Andreas Anastasiou and Angelos Papanastasiou Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences . . . . . . . . . . . . . ?? Rémi Boutin and Charles Bouveyron and Pierre Latouche Embedded topics in the stochastic block model . . . . . . . . . . . . . . . . . ?? Ruiqi Liu and Ganggang Xu and Zuofeng Shang Distributed adaptive nearest neighbor classifier: algorithm and theory . . . . ?? Xinzhu Liang and Shangda Yang and Simon L. Cotter and Kody J. H. Law A randomized multi-index sequential Monte Carlo method . . . . . . . . . . . ?? Marta Crispino and Cristina Mollica and Valerio Astuti and Luca Tardella Efficient and accurate inference for mixtures of Mallows models with Spearman distance . . . . . . . . . . . . . . . . ?? Maicon J. Karling and Marc G. Genton and Simos G. Meintanis Goodness-of-fit tests for multivariate skewed distributions based on the characteristic function . . . . . . . . ?? Jessica E. Forsyth and Ali H. Al-Anbaki and Berenika Plusa and Simon L. Cotter Unlabelled landmark matching via Bayesian data selection, and application to cell matching across imaging modalities . . . . . . . . . . . . . . . ?? Xinmin Li and Haozhe Liang and Wolfgang Härdle and Hua Liang Use generalized linear models or generalized partially linear models? . . ?? Yanxin Li and Antonio Linero and Stephen G. Walker Latent uniform samplers on multivariate binary spaces . . . . . . . . . . . . . ?? Julien Demange-Chryst and François Bachoc and Jérôme Morio Efficient estimation of multiple expectations with the same sample by adaptive importance sampling and control variates . . . . . . . . . . . . . . . . ?? Gonzalo Vicente and Aritz Adin and Tomás Goicoa and Mar\'ìa Dolores Ugarte High-dimensional order-free multivariate spatial disease mapping . . . . . . . . ?? Jason Hou-Liu and Ryan P. Browne Generalized linear models for massive data via doubly-sketching . . . . . . . ?? Michail Tsagris and Abdulaziz Alenazi and Connie Stewart Flexible non-parametric regression models for compositional response data with zeros . . . . . . . . . . . . . . . ?? Eduardo García-Portugués and Arturo Prieto-Tirado Toroidal PCA via density ridges . . . . ?? Henry Antonio Palasciano and Guy P. Nason A test for the absence of aliasing or white noise in two-dimensional locally stationary wavelet processes . . . . . . ?? Tomás Mrkvicka and Mari Myllymäki False discovery rate envelopes . . . . . ?? Dean A. Bodenham and Yoshinobu Kawahara euMMD: efficiently computing the MMD two-sample test statistic for univariate data . . . . . . . . . . . . . . . . . . ?? Mary Llewellyn and Ruth King and V\'ìctor Elvira and Gordon Ross A point mass proposal method for Bayesian state-space model fitting . . . ?? Samuel I. Watson and Yi Pan Evaluation of combinatorial optimisation algorithms for $c$-optimal experimental designs with correlated observations . . ?? Yan Li and Na Han and Yuxiang Qin and Jing Zhang and Jinxia Su Trans-cGAN: transformer-Unet-based generative adversarial networks for cross-modality magnetic resonance image synthesis . . . . . . . . . . . . . . . ?? Yao Shi and Wanchunzi Yu and John Stufken Optimal designs for generalized linear mixed models based on the penalized quasi-likelihood method . . . . . . . . ?? Danilo Alvares and Valeria Leiva-Yamaguchi A two-stage approach for Bayesian joint models: reducing complexity while maintaining accuracy . . . . . . . . . . ?? Ibrahim Merad and Stéphane Ga\"\iffas Robust supervised learning with coordinate gradient descent . . . . . . ?? Jiahui Zou and Chaoxia Yuan and Xinyu Zhang and Guohua Zou and Alan T. K. Wan Model averaging for support vector classifier by cross-validation . . . . . ?? Sidi Wu and Cédric Beaulac and Jiguo Cao Neural networks for scalar input and functional output . . . . . . . . . . . ??
Junhan Fang and Grace Y. Yi Bayesian analysis for matrix-variate logistic regression with/without response misclassification . . . . . . . ??
Kin Yap Cheung and Stephen M. S. Lee High-dimensional local polynomial regression with variable selection and dimension reduction . . . . . . . . . . ?? Kipoong Kim and Sungkyu Jung Integrative sparse reduced-rank regression via orthogonal rotation for analysis of high-dimensional multi-source data . . . . . . . . . . . ?? Liugen Xue Empirical likelihood and estimation in single-index varying-coefficient models with censored data . . . . . . . . . . . ?? Xin Li and Dongya Wu Sparse estimation in high-dimensional linear errors-in-variables regression via a covariate relaxation method . . . ?? Issam-Ali Moindjié and Sophie Dabo-Niang and Cristian Preda Classification of multivariate functional data on different domains with Partial Least Squares approaches ?? Ines Ortega-Fernandez and Marta Sestelo and Nora M. Villanueva Explainable generalized additive neural networks with independent neural network training . . . . . . . . . . . . . . . . ?? Arjun Lakra and Buddhananda Banerjee and Arnab Kumar Laha A data-adaptive method for outlier detection from functional data . . . . . ?? Jingjing Jiang and Chunjie Wang and Deng Pan and Xinyuan Song Transformation models with informative partly interval-censored data . . . . . ?? Lucca Portes Cavalheiro and Simon Bernard and Jean Paul Barddal and Laurent Heutte Random forest kernel for high-dimension low sample size classification . . . . . ?? Hsin-Hsiung Huang and Feng Yu and Xing Fan and Teng Zhang A framework of regularized low-rank matrix models for regression and classification . . . . . . . . . . . . . ?? Dmytro Perepolkin and Benjamin Goodrich and Ullrika Sahlin Hybrid elicitation and quantile-parametrized likelihood . . . . ?? Michaël Allouche and Stéphane Girard and Emmanuel Gobet Estimation of extreme quantiles from heavy-tailed distributions with neural networks . . . . . . . . . . . . . . . . ?? Carlos Tadeu Pagani Zanini and Helio S. Migon and Ronaldo Dias Variational inference for Bayesian bridge regression . . . . . . . . . . . ?? Rahul Biswas and Somabha Mukherjee Consistent causal inference from time series with PC algorithm and its time-aware extension . . . . . . . . . . ?? Takahiro Onizuka and Shintaro Hashimoto and Shonosuke Sugasawa Fast and locally adaptive Bayesian quantile smoothing using calibrated variational approximations . . . . . . . ?? Pedro L. Ramos and Nixon Jerez-Lillo and Francisco A. Segovia and Osafu A. Egbon and Francisco Louzada Power-law distribution in pieces: a semi-parametric approach with change point detection . . . . . . . . . . . . ?? Shrijita Bhattacharya and Zihuan Liu and Tapabrata Maiti Comprehensive study of variational Bayes classification for dense deep neural networks . . . . . . . . . . . . . . . . ?? Marco Alf\`o and Nicola Salvati and Ranalli M. Giovanna Correction to: Finite mixtures of quantile and $M$-quantile regression models . . . . . . . . . . . . . . . . . ?? Deepak Prajapati and Ayan Pal and Debasis Kundu A finite mixture model for multiple dependent competing risks with applications of automotive warranty claims data . . . . . . . . . . . . . . ?? Daniel Rudolf and Philip Schär Dimension-independent spectral gap of polar slice sampling . . . . . . . . . . ?? Lorenzo Zambon and Dario Azzimonti and Giorgio Corani Efficient probabilistic reconciliation of forecasts for real-valued and count time series . . . . . . . . . . . . . . ?? M. Barroso and C. M. Alaíz and J. L. Torrecilla and A. Fernández Functional diffusion maps . . . . . . . ?? Wanwan Liang and Ben Wu and Bo Zhang Modeling volatility for high-frequency data with rounding error: a nonparametric Bayesian approach . . . . ?? Rongqian Sun and Xinyuan Song Bayesian tree-based heterogeneous mediation analysis with a time-to-event outcome . . . . . . . . . . . . . . . . ?? Luis E. Nieto-Barajas Multivariate and regression models for directional data based on projected Pólya trees . . . . . . . . . . . . . . . . . ?? Aisha Fayomi and Yannis Pantazis and Michail Tsagris and Andrew T. A. Wood Cauchy robust principal component analysis with applications to high-dimensional data sets . . . . . . . ?? Alexander Aushev and Thong Tran and Henri Pesonen and Andrew Howes and Samuel Kaski Likelihood-free inference in state-space models with unknown dynamics . . . . . . ?? Michael Grabchak and Xingnan Zhang Representation and simulation of multivariate Dickman distributions and Vervaat perpetuities . . . . . . . . . . ?? Gavin Collins and Devin Francom and Kellin Rumsey Bayesian projection pursuit regression ?? Jorge Loría and Anindya Bhadra SURE-tuned bridge regression . . . . . . ?? Schalk Daniel and Bischl Bernd and Rügamer David Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models . . . . . . . . . . . . . . ?? Tabea Rebafka Model-based clustering of multiple networks with a hierarchical algorithm ?? Yaman Kindap and Simon Godsill Point process simulation of generalised hyperbolic Lévy processes . . . . . . . . ?? Pawe\l D\lotko and Niklas Hellmer and \Lukasz Stettner and Rafa\l Topolnicki Topology-driven goodness-of-fit tests in arbitrary dimensions . . . . . . . . . . ?? Guanhua Fang and Owen G. Ward and Tian Zheng Online estimation and community detection of network point processes for event streams . . . . . . . . . . . . . ?? Yeonjoo Park and Hee-Seok Oh and Yaeji Lim A data-adaptive dimension reduction for functional data via penalized low-rank approximation . . . . . . . . . . . . . ?? David Oechsler Lévy Langevin Monte Carlo . . . . . . . . ?? Rakhi Singh Pareto-efficient designs for multi- and mixed-level supersaturated designs . . . ?? Liugen Xue Doubly robust estimation and robust empirical likelihood in generalized linear models with missing responses . . ?? Chunhui Liang and Wenqing Ma Heterogeneous analysis for clustered data using grouped finite mixture models ?? Weiwei Wang and Yuqiang Li and Xianyi Wu Off-policy evaluation for tabular reinforcement learning with synthetic trajectories . . . . . . . . . . . . . . ?? M. Alfó and M. F. Marino and F. Martella Biclustering multivariate discrete longitudinal data . . . . . . . . . . . ?? Yan Chen and Shuixin Fang and Lu Lin Renewable composite quantile method and algorithm for nonparametric models with streaming data . . . . . . . . . . . . . ?? Bernard W. Silverman and Lax Chan and Kyle Vincent Bootstrapping multiple systems estimates to account for model selection . . . . . ?? Hanwen Xuan and Luca Maestrini and Feng Chen and Clara Grazian Stochastic variational inference for GARCH models . . . . . . . . . . . . . . ?? Jan Vávra and Arno\vst Komárek and Bettina Grün and Gertraud Malsiner-Walli Clusterwise multivariate regression of mixed-type panel data . . . . . . . . . ?? Shang-Ying Shiu and Yen-Shiu Chin and Szu-Han Lin and Ting-Li Chen Randomized self-updating process for clustering large-scale data . . . . . . ?? Peter A. Whalley and Daniel Paulin and Benedict Leimkuhler Randomized time Riemannian Manifold Hamiltonian Monte Carlo . . . . . . . . ?? Laixu Shang and Qian-Zhen Zheng and Ping-Feng Xu and Na Shan and Man-Lai Tang A generalized expectation model selection algorithm for latent variable selection in multidimensional item response theory models . . . . . . . . . ?? David J. Warne and Oliver J. Maclaren and Elliot J. Carr and Matthew J. Simpson and Christopher Drovandi Generalised likelihood profiles for models with intractable likelihoods . . ?? Linh H. Nghiem and Francis K. C. Hui and Samuel Muller and A. H. Welsh Likelihood-based surrogate dimension reduction . . . . . . . . . . . . . . . ?? Hung-Kai Pi and Mei-Hui Guo and Ray-Bing Chen and Shih-Feng Huang ECOPICA: empirical copula-based independent component analysis . . . . . ?? Marion Naveau and Guillaume Kon Kam King and Renaud Rincent and Laure Sansonnet and Maud Delattre Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm . . . . ?? Étienne David and Jean Bellot and Sylvain Le Corff and Luc Lehéricy Identifiability of discrete input-output hidden Markov models with external signals . . . . . . . . . . . . . . . . ?? Antoine Godichon-Baggioni and Stéphane Robin A robust model-based clustering based on the geometric median and the median covariation matrix . . . . . . . . . . . ?? Yuhyeong Jang and Raanju R. Sundararajan and Wagner Barreto-Souza A multivariate heavy-tailed integer-valued GARCH process with EM algorithm-based inference . . . . . . . ?? Noa Kallioinen and Topi Paananen and Paul-Christian Bürkner and Aki Vehtari Detecting and diagnosing prior and likelihood sensitivity with power-scaling . . . . . . . . . . . . . ?? Alexandre Mösching and Lutz Dümbgen Estimation of a likelihood ratio ordered family of distributions . . . . . . . . ?? Kai Yang and Masoud Asgharian and Sahir Bhatnagar Accelerated gradient methods for sparse statistical learning with nonconvex penalties . . . . . . . . . . . . . . . ?? Frank Nielsen and Kazuki Okamura On the $f$-divergences between densities of a multivariate location or scale family . . . . . . . . . . . . . . . . . ?? Filippo Pagani and Augustin Chevallier and Sam Power and Thomas House and Simon Cotter NuZZ: Numerical Zig-Zag for general models . . . . . . . . . . . . . . . . . ??
Luca Brusa and Fulvia Pennoni and Francesco Bartolucci Maximum likelihood estimation for discrete latent variable models via evolutionary algorithms . . . . . . . . ?? Naruesorn Prabpon and Kitakorn Homsud and Pat Vatiwutipong Nonparametric Bayesian online change point detection using kernel density estimation with nonparametric hazard function . . . . . . . . . . . . . . . . ?? Etienne Côme Bayesian contiguity constrained clustering . . . . . . . . . . . . . . . ?? Cheng-Der Fuh and Chuan-Ju Wang Efficient exponential tilting with applications . . . . . . . . . . . . . . ?? Beatrice Foroni and Luca Merlo and Lea Petrella Expectile hidden Markov regression models for analyzing cryptocurrency returns . . . . . . . . . . . . . . . . ?? Chengqian Xian and Camila P. E. de Souza and Wenqing He and Felipe F. Rodrigues and Renfang Tian Variational Bayesian analysis of survival data using a log-logistic accelerated failure time model . . . . . ?? Luke Mosley and Tak-Shing T. Chan and Alex Gibberd The sparse dynamic factor model: a regularised quasi-maximum likelihood approach . . . . . . . . . . . . . . . . ?? Shan Lu and Wenjing Wang and Rong Guan Kent feature embedding for classification of compositional data with zeros . . . . . . . . . . . . . . . ?? Hongyu Wu and Jonathan R. Bradley Global-local shrinkage multivariate logit-beta priors for multiple response-type data . . . . . . . . . . . ?? Carlos Echegoyen and Aritz Pérez and Guzmán Santafé and Unai Pérez-Goya and María Dolores Ugarte Large-scale unsupervised spatio-temporal semantic analysis of vast regions from satellite images sequences . . . . . . . ?? Keith Levin and Brenda Betancourt Fast generation of exchangeable sequences of clusters data . . . . . . . ?? Jose Ameijeiras-Alonso A reliable data-based smoothing parameter selection method for circular kernel estimation . . . . . . . . . . . ?? Matheus Castro and Caio Azevedo and Juvêncio Nobre A robust quantile regression for bounded variables based on the Kumaraswamy Rectangular distribution . . . . . . . . ?? Sarat Moka and Benoit Liquet and Houying Zhu and Samuel Muller COMBSS: best subset selection via continuous optimization . . . . . . . . ?? Esam Mahdi New mixed portmanteau tests for time series models . . . . . . . . . . . . . ?? Zehan Yang and HaiYing Wang and Jun Yan Subsampling approach for least squares fitting of semi-parametric accelerated failure time models to massive survival data . . . . . . . . . . . . . . . . . . ?? Ajay Jasra and Hamza Ruzayqat and Amin Wu Bayesian parameter inference for partially observed stochastic Volterra equations . . . . . . . . . . . . . . . ?? Yushan Xue and Jie Ren and Bin Yang Enmsp: an elastic-net multi-step screening procedure for high-dimensional regression . . . . . . . . . . . . . . . ?? Wan Tian and Zhongfeng Qin The minimum covariance determinant estimator for interval-valued data . . . ?? Francesco Amato and Julien Jacques and Isabelle Prim-Allaz Clustering longitudinal ordinal data via finite mixture of matrix-variate distributions . . . . . . . . . . . . . ?? Nicholas Kissel and Lucas Mentch Forward stability and model path selection . . . . . . . . . . . . . . . ?? Yannis G. Yatracos Do applied statisticians prefer more randomness or less? Bootstrap or Jackknife? . . . . . . . . . . . . . . . ?? Yuki Takazawa and Tomonari Sei Maximum likelihood estimation of log-concave densities on tree space . . ?? Alex Ziyu Jiang and Abel Rodriguez Improvements on scalable stochastic Bayesian inference methods for multivariate Hawkes process . . . . . . ?? Xin Chen and Chang Deng and Shuaida He and Runxiong Wu and Jia Zhang High-dimensional sparse single-index regression via Hilbert--Schmidt independence criterion . . . . . . . . . ?? Emanuele Borgonovo and Elmar Plischke and Clémentine Prieur Total effects with constrained features ?? Thomas Lux Estimation of regime-switching diffusions via Fourier transforms . . . ?? Ruiting Hao and Xiaorong Yang Multiple-output quantile regression neural network . . . . . . . . . . . . . ?? Hanâ Lbath and Alexander Petersen and Sophie Achard Large-scale correlation screening under dependence for brain functional connectivity network inference . . . . . ?? Alessandro Celani and Paolo Pagnottoni and Galin Jones Bayesian variable selection for matrix autoregressive models . . . . . . . . . ?? Xinyu Zhang and Hongwei Shi and Niwen Zhou and Falong Tan and Xu Guo Quantile generalized measures of correlation . . . . . . . . . . . . . . ?? Janice L. Scealy and Kassel L. Hingee and John T. Kent and Andrew T. A. Wood Robust score matching for compositional data . . . . . . . . . . . . . . . . . . ?? Alessio Farcomeni and Marco Geraci Quantile ratio regression . . . . . . . ??
Fengchuan Zhang and Sanguo Zhang and Shi-Ming Li and Mingyang Ren Matrix regression heterogeneity analysis ?? Xia Junwen and Zhan Zishu and Zhang Jingxiao Doubly robust estimation of optimal treatment regimes for survival data using an instrumental variable . . . . . ?? Ian Meneghel Danilevicz and Valdério Anselmo Reisen and Pascal Bondon Expectile and $M$-quantile regression for panel data . . . . . . . . . . . . . ?? Fa\"\icel Chamroukhi and Nhat Thien Pham and Van H\`a Hoang and Geoffrey J. McLachlan Functional mixtures-of-experts . . . . . ?? Kes Ward and Gaetano Romano and Idris Eckley and Paul Fearnhead A constant-per-iteration likelihood ratio test for online changepoint detection for exponential family models ?? David Rodríguez-Vítores and Carlos Matrán Improving model choice in classification: an approach based on clustering of covariance matrices . . . ?? Jasmin Rühl and Sarah Friedrich Resampling-based confidence intervals and bands for the average treatment effect in observational studies with competing risks . . . . . . . . . . . . ?? Jungmin Shin and Seunghyun Gwak and Seung Jun Shin and Sungwan Bang Simultaneous estimation and variable selection for a non-crossing multiple quantile regression using deep neural networks . . . . . . . . . . . . . . . . ?? Abdelaati Daouia and Gilles Stupfler and Antoine Usseglio-Carleve An expectile computation cookbook . . . ?? Sarah Leyder and Jakob Raymaekers and Tim Verdonck Generalized spherical principal component analysis . . . . . . . . . . . ?? Youwu Lin and Xin Zeng and Pei Wang and Shuai Huang and Kok Lay Teo Variable selection using axis-aligned random projections for partial least-squares regression . . . . . . . . ?? Seungwoo Kang and Hee-Seok Oh Novel sampling method for the von Mises--Fisher distribution . . . . . . . ?? Chen Ouyang and Chenkaixiang Lu and Xiong Zhao and Ruping Huang and Gonglin Yuan and Yiyan Jiang Stochastic three-term conjugate gradient method with variance technique for non-convex learning . . . . . . . . . . ?? Carlo Cavicchia and Maurizio Vichi and Giorgia Zaccaria Parsimonious ultrametric Gaussian mixture models . . . . . . . . . . . . . ?? Jonathan James Automated generation of initial points for adaptive rejection sampling of log-concave distributions . . . . . . . ?? Bao Anh Vu and David Gunawan and Andrew Zammit-Mangion R-VGAL: a sequential variational Bayes algorithm for generalised linear mixed models . . . . . . . . . . . . . . . . . ?? Frank Rotiroti and Stephen G. Walker Reversed particle filtering for hidden Markov models . . . . . . . . . . . . . ?? Xuejun Jiang and Yakun Liang and Haofeng Wang Screen then select: a strategy for correlated predictors in high-dimensional quantile regression . . ?? Marion Naveau and Guillaume Kon Kam King and Renaud Rincent and Laure Sansonnet and Maud Delattre Correction to: Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm . . . . . . . . . . . . . . . ?? Ilaria Bombelli and Maurizio Vichi Parsimonious consensus hierarchies, partitions and fuzzy partitioning of a set of hierarchies . . . . . . . . . . . ?? Ziyang Yang and Idris A. Eckley and Paul Fearnhead A communication-efficient, online changepoint detection method for monitoring distributed sensor networks ?? Joaquín Martínez-Minaya and Haavard Rue A flexible Bayesian tool for CoDa mixed models: logistic-normal distribution with Dirichlet covariance . . . . . . . ?? Dongrak Choi and Woojung Bae and Jun Yan and Sangwook Kang A general model-checking procedure for semiparametric accelerated failure time models . . . . . . . . . . . . . . . . . ?? Yu-Chien Bo Ning and Ning Ning Spike and slab Bayesian sparse principal component analysis . . . . . . . . . . . ??
Alex Cooper and Aki Vehtari and Catherine Forbes and Dan Simpson and Lauren Kennedy Bayesian cross-validation by parallel Markov chain Monte Carlo . . . . . . . . ?? Vladimir Pastukhov Fused lasso nearly-isotonic signal approximation in general dimensions . . ?? Matthias Templ Robust multiple imputation with GAM . . ?? Zuoxun Tan and Hu Yang Group sparse structural smoothing recovery: model, statistical properties and algorithm . . . . . . . . . . . . . ?? Eoghan O'Neill Type I Tobit Bayesian Additive Regression Trees for censored outcome regression . . . . . . . . . . . . . . . ?? Mineaki Ohishi Generalized fused Lasso for grouped data in generalized linear models . . . . . . ?? Sphiwe B. Skhosana and Salomon M. Millard and Frans H. J. Kanfer A modified EM-type algorithm to estimate semi-parametric mixtures of non-parametric regressions . . . . . . . ?? Antoine Luciano and Christian P. Robert and Robin J. Ryder Insufficient Gibbs sampling . . . . . . ?? Gianluca Cubadda and Francesco Giancaterini and Alain Hecq and Joann Jasiak Optimization of the generalized covariance estimator in noncausal processes . . . . . . . . . . . . . . . ?? Ruhul Ali Khan and Ayan Pal and Debasis Kundu Testing the goodness-of-fit of the stable distributions with applications to German stock index data and Bitcoin cryptocurrency data . . . . . . . . . . ?? Douglas P. Wiens Jittering and clustering: strategies for the construction of robust designs . . . ?? Abdelaati Daouia and Gilles Stupfler and Antoine Usseglio-Carleve Bias-reduced and variance-corrected asymptotic Gaussian inference about extreme expectiles . . . . . . . . . . . ?? H. Chau and J. L. Kirkby and D. H. Nguyen and D. Nguyen and N. Nguyen and T. Nguyen An efficient method to simulate diffusion bridges . . . . . . . . . . . ?? Yann McLatchie and Aki Vehtari Efficient estimation and correction of selection-induced bias with order statistics . . . . . . . . . . . . . . . ?? Xiaoyan Li and Xiaochao Xia and Zhimin Zhang Poisson subsampling-based estimation for growing-dimensional expectile regression in massive data . . . . . . . . . . . . ?? Rafael Flock and Yiqiu Dong and Felipe Uribe and Olivier Zahm Certified coordinate selection for high-dimensional Bayesian inversion with Laplace prior . . . . . . . . . . . . . ?? Aude Sportisse and Matthieu Marbac and Fabien Laporte and Gilles Celeux and Claire Boyer and Julie Josse and Christophe Biernacki Model-based clustering with missing not at random data . . . . . . . . . . . . . ?? Brieuc Lehmann and Simon White A Bayesian multilevel model for populations of networks using exponential-family random graphs . . . . ?? Silius M. Vandeskog and Sara Martino and Raphaël Huser An efficient workflow for modelling high-dimensional spatial extremes . . . ?? Patrick Zietkiewicz and Ioannis Kosmidis Bounded-memory adjusted scores estimation in generalized linear models with large data sets . . . . . . . . . . ?? Tianming Bai and Aretha L. Teckentrup and Konstantinos C. Zygalakis Gaussian processes for Bayesian inverse problems associated with linear partial differential equations . . . . . . . . . ?? Rémy Abergel and Olivier Bouaziz and Grégory Nuel A review on the Adaptive-Ridge Algorithm with several extensions . . . . . . . . ?? Diego I. Gallardo and Marcelo Bourguignon and José S. Romeo Birnbaum--Saunders frailty regression models for clustered survival data . . . ?? Wisdom Aselisewine and Suvra Pal Enhancing cure rate analysis through integration of machine learning models: a comparative study . . . . . . . . . . ?? Sarah Elizabeth Heaps and Ian Hyla Jermyn Structured prior distributions for the covariance matrix in latent factor models . . . . . . . . . . . . . . . . . ?? Weitao Hu and Weiping Zhang Flexible Bayesian quantile regression based on the generalized asymmetric Huberised-type distribution . . . . . . ?? Douglas O. Cardoso and João Domingos Gomes da Silva Junior and Carla Silva Oliveira and Celso Marques and Laura Silva de Assis Greedy recursive spectral bisection for modularity-bound hierarchical divisive community detection . . . . . . . . . . ??
Jonas Latz Correction to: Analysis of stochastic gradient descent in continuous time . . ?? Ning Ning and Edward Ionides Systemic infinitesimal over-dispersion on graphical dynamic models . . . . . . ?? Hu Jiang and Liu Yiming and Zhou Wang On weak convergence of quantile-based empirical likelihood process for ROC curves . . . . . . . . . . . . . . . . . ?? Logan Bell and Nikhil Devanathan and Stephen Boyd Efficient Shapley performance attribution for least-squares regression ?? Sude Gurer and Han Lin Shang and Abhijit Mandal and Ufuk Beyaztas Locally sparse and robust partial least squares in scalar-on-function regression ?? Fabiana Camattari and Sabrina Guastavino and Francesco Marchetti and Michele Piana and Emma Perracchione Classifier-dependent feature selection via greedy methods . . . . . . . . . . . ?? Siu-Kui Au A limit formula and a series expansion for the bivariate normal tail probability . . . . . . . . . . . . . . ?? Ines Ortega-Fernandez and Marta Sestelo and Nora M. Villanueva Correction to: Explainable generalized additive neural networks with independent neural network training . . ?? Jean Steve Tamo Tchomgui and Julien Jacques and Guillaume Fraysse and Vincent Barriac and Stéphane Chretien A mixture of experts regression model for functional response with functional covariates . . . . . . . . . . . . . . . ?? Louis Ohl and Pierre-Alexandre Mattei and Charles Bouveyron and Mickaël Leclercq and Arnaud Droit and Frédéric Precioso Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection . . . . . . . . . . . . . . . ?? Elvis Han Cui and Zizhao Zhang and Weng Kee Wong Optimal designs for nonlinear mixed-effects models using competitive swarm optimizer with mutated agents . . ?? Yifei Huang and Keren Li and Abhyuday Mandal and Jie Yang ForLion: a new algorithm for $D$-optimal designs under general parametric statistical models with mixed factors ?? Canyi Chen and Zhengtian Zhu Byzantine-robust and efficient distributed sparsity learning: a surrogate composite quantile regression approach . . . . . . . . . . . . . . . . ?? Jie Zeng and Guozhi Hu and Weihu Cheng A Mallows-type model averaging estimator for ridge regression with randomly right censored data . . . . . . . . . . . . . ?? Yoonah Lee and Seongoh Park High-dimensional missing data imputation via undirected graphical model . . . . . ?? Xiaoyan Li and Xiaochao Xia and Zhimin Zhang Distributed subsampling for multiplicative regression . . . . . . . ?? Michael J. Hollaway and Rebecca Killick Detection of spatiotemporal changepoints: a generalised additive model approach . . . . . . . . . . . . . ?? Guangbao Guo and Haoyue Song and Lixing Zhu The COR criterion for optimal subset selection in distributed estimation . . ?? Marcel Hirt and Vasileios Kreouzis and Petros Dellaportas Learning variational autoencoders via MCMC speed measures . . . . . . . . . . ?? Anna De Magistris and Valentina De Simone and Elvira Romano and Gerardo Toraldo Roughness regularization for functional data analysis with free knots spline estimation . . . . . . . . . . . . . . . ?? Hyejoon Park and Hyunjoong Kim AR-ADASYN: angle radius-adaptive synthetic data generation approach for imbalanced learning . . . . . . . . . . ?? Anne Poot and Pierre Kerfriden and Iuri Rocha and Frans van der Meer A Bayesian approach to modeling finite element discretization error . . . . . . ?? Simon Pfahler and Peter Georg and Rudolf Schill and Maren Klever and Lars Grasedyck and Rainer Spang and Tilo Wettig Taming numerical imprecision by adapting the KL divergence to negative probabilities . . . . . . . . . . . . . ?? Bao Anh Vu and David Gunawan and Andrew Zammit-Mangion Correction to: R-VGAL: a sequential variational Bayes algorithm for generalised linear mixed models . . . . ?? Cheng Huan and Xinyuan Song and Hongwei Yuan Individualized causal mediation analysis with continuous treatment using conditional generative adversarial networks . . . . . . . . . . . . . . . . ?? Mario Beraha and Matteo Pegoraro Wasserstein principal component analysis for circular measures . . . . . . . . . ?? Bu Zhou and Zhi Peng Ong and Jin-Ting Zhang A new maximum mean discrepancy based two-sample test for equal distributions in separable metric spaces . . . . . . . ?? Ingvild M. Helgòy and Hans J. Skaug and Yushu Li Sparse Bayesian learning using TMB (Template Model Builder) . . . . . . . . ?? Samuel Stockman and Daniel J. Lawson and Maximilian J. Werner SB-ETAS: using simulation based inference for scalable, likelihood-free inference for the ETAS model of earthquake occurrences . . . . . . . . . ?? Huiling Liu and Xinmin Li and Feifei Chen and Wolfgang Härdle and Hua Liang A comprehensive comparison of goodness-of-fit tests for logistic regression models . . . . . . . . . . . ?? Shuang Dai and Ping Wu and Zhou Yu New forest-based approaches for sufficient dimension reduction . . . . . ?? Almog Peer and David Azriel Optimal confidence interval for the difference between proportions . . . . . ?? Subhrajyoty Roy and Abhik Ghosh and Ayanendranath Basu Robust singular value decomposition with application to video surveillance background modelling . . . . . . . . . . ??
Guangbao Guo and Haoyue Song and Lixing Zhu Correction to: The COR criterion for optimal subset selection in distributed estimation . . . . . . . . . . . . . . . ?? Jiawei Wen and Songshan Yang and Delin Zhao Nonconvex Dantzig selector and its parallel computing algorithm . . . . . . ?? Julyan Arbel and Stéphane Girard and Hadrien Lorenzo Shrinkage for extreme partial least-squares . . . . . . . . . . . . . ??