Last update:
Mon Mar 18 07:55:21 MDT 2024
David 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 . . . . . ??