Table of contents for issues of Bayesian Analysis

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Volume 1, Number 1, March, 2006
Volume 1, Number 2, June, 2006
Volume 1, Number 3, September, 2006
Volume 1, Number 4, December, 2006
Volume 2, Number 1, March, 2007
Volume 2, Number 2, June, 2007
Volume 2, Number 3, September, 2007
Volume 2, Number 4, December, 2007
Volume 3, Number 1, March, 2008
Volume 3, Number 2, June, 2008
Volume 3, Number 3, September, 2008
Volume 3, Number 4, December, 2008
Volume 4, Number 1, March, 2009
Volume 4, Number 2, June, 2009
Volume 4, Number 3, September, 2009
Volume 4, Number 4, December, 2009
Volume 5, Number 1, March, 2010
Volume 5, Number 2, June, 2010
Volume 5, Number 3, September, 2010
Volume 5, Number 4, December, 2010
Volume 6, Number 1, March, 2011
Volume 6, Number 2, June, 2011
Volume 6, Number 3, September, 2011
Volume 6, Number 4, December, 2011
Volume 7, Number 1, March, 2012
Volume 7, Number 2, June, 2012
Volume 7, Number 3, September, 2012
Volume 7, Number 4, December, 2012
Volume 8, Number 1, March, 2013
Volume 8, Number 2, June, 2013
Volume 8, Number 3, September, 2013
Volume 8, Number 4, December, 2013
Volume 9, Number 1, March, 2014
Volume 9, Number 2, June, 2014
Volume 9, Number 3, September, 2014
Volume 9, Number 4, December, 2014
Volume 10, Number 1, March, 2015
Volume 10, Number 2, June, 2015
Volume 10, Number 3, September, 2015
Volume 10, Number 4, December, 2015
Volume 11, Number 1, March, 2016
Volume 11, Number 2, June, 2016
Volume 11, Number 3, September, 2016
Volume 11, Number 4, December, 2016
Volume 12, Number 1, March, 2017
Volume 12, Number 2, June, 2017
Volume 12, Number 3, September, 2017
Volume 12, Number 4, December, 2017
Volume 13, Number 1, March, 2018
Volume 13, Number 2, June, 2018
Volume 13, Number 3, September, 2018
Volume 13, Number 4, December, 2018


Bayesian Analysis
Volume 1, Number 1, March, 2006

            Stephen E. Fienberg   When did Bayesian inference become
                                  ``Bayesian''?  . . . . . . . . . . . . . 1--40
            Alan E. Gelfand and   
      John A. Silander, Jr. and   
                Shanshan Wu and   
             Andrew Latimer and   
              Paul O. Lewis and   
          Anthony G. Rebelo and   
                    Mark Holder   Explaining species distribution patterns
                                  through hierarchical modeling  . . . . . 41--92
            Jennifer A. Hoeting   Some perspectives on modeling species
                                  distributions (comment on article by
                                  Gelfand et al.)  . . . . . . . . . . . . 93--97
                Jay M. Ver Hoef   Comment on article by Gelfand et al. . . 99--101
            Alan E. Gelfand and   
      John A. Silander, Jr. and   
                Shanshan Wu and   
             Andrew Latimer and   
              Paul O. Lewis and   
          Anthony G. Rebelo and   
                    Mark Holder   Rejoinder  . . . . . . . . . . . . . . . 103--104
            Leanna L. House and   
           Merlise A. Clyde and   
              Yuh-Chin T. Huang   Bayesian Identification of Differential
                                  Gene Expression Induced by Metals in
                                  Human Bronchial Epithelial Cells . . . . 105--120
              David M. Blei and   
              Michael I. Jordan   Variational inference for Dirichlet
                                  process mixtures . . . . . . . . . . . . 121--143
            Chris C. Holmes and   
                  Leonhard Held   Bayesian auxiliary variable models for
                                  binary and multinomial regression  . . . 145--168
           J. A. A. Andrade and   
                     A. O'Hagan   Bayesian robustness modeling using
                                  regularly varying distributions  . . . . 169--188
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Bayesian Analysis
Volume 1, Number 2, June, 2006

           David A. van Dyk and   
             Alanna Connors and   
              David N. Esch and   
              Peter Freeman and   
                Hosung Kang and   
         Margarita Karovska and   
              Vinay Kashyap and   
        Aneta Siemiginowska and   
                  Andreas Zezas   Deconvolution in High-Energy
                                  Astrophysics: Science, Instrumentation,
                                  and Methods  . . . . . . . . . . . . . . 189--235
                Ji Meng Loh and   
                  Andrew Gelman   Comment on article by van Dyk et al. . . 237--240
           David A. van Dyk and   
                    Hosung Kang   Rejoinder  . . . . . . . . . . . . . . . 241--248
          Herbert K. H. Lee and   
         Bruno Sansó and   
               Weining Zhou and   
                David M. Higdon   Inferring Particle Distribution in a
                                  Proton Accelerator Experiment  . . . . . 249--264
            Caitlin E. Buck and   
Delil Gómez Portugal Aguilar and   
            Cliff D. Litton and   
                Anthony O'Hagan   Bayesian nonparametric estimation of the
                                  radiocarbon calibration curve  . . . . . 265--288
         Edoardo M. Airoldi and   
       Annelise G. Anderson and   
        Stephen E. Fienberg and   
               Kiron K. Skinner   Who wrote Ronald Reagan's radio
                                  addresses? . . . . . . . . . . . . . . . 289--319
                  Peter D. Hoff   Model-based subspace clustering  . . . . 321--344
        Suhrid Balakrishnan and   
                  David Madigan   A one-pass sequential Monte Carlo method
                                  for Bayesian analysis of massive
                                  datasets . . . . . . . . . . . . . . . . 345--361
           Joseph B. Kadane and   
              Galit Shmueli and   
            Thomas P. Minka and   
               Sharad Borle and   
               Peter Boatwright   Conjugate Analysis of the
                                  Conway--Maxwell--Poisson Distribution    363--374
        Christopher J. Paciorek   Misinformation in the conjugate prior
                                  for the linear model with implications
                                  for free-knot spline modelling . . . . . 375--383
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Bayesian Analysis
Volume 1, Number 3, September, 2006

                   James Berger   The Case for Objective Bayesian Analysis 385--402
              Michael Goldstein   Subjective Bayesian Analysis: Principles
                                  and Practice . . . . . . . . . . . . . . 403--420
      J. Andrés Christen   Stop using `subjective' to refer to
                                  Bayesian analyses (comment on articles
                                  by Berger and by Goldstein)  . . . . . . 421--422
                   David Draper   Coherence and calibration: comments on
                                  subjectivity and ``objectivity'' in
                                  Bayesian analysis (comment on articles
                                  by Berger and by Goldstein)  . . . . . . 423--428
            Stephen E. Fienberg   Does it make sense to be an ``objective
                                  Bayesian''? (comment on articles by
                                  Berger and by Goldstein) . . . . . . . . 429--432
               Joseph B. Kadane   Is ``objective Bayesian analysis''
                                  objective, Bayesian, or wise? (comment
                                  on articles by Berger and by Goldstein)  433--436
                 Robert E. Kass   Kinds of Bayesians (comment on articles
                                  by Berger and by Goldstein)  . . . . . . 437--440
                      Frank Lad   Objective Bayesian statistics \ldots. Do
                                  you buy it? Should we sell it? (comment
                                  on articles by Berger and by Goldstein)  441--444
                Anthony O'Hagan   Science, subjectivity and software
                                  (comment on articles by Berger and by
                                  Goldstein) . . . . . . . . . . . . . . . 445--450
                Larry Wasserman   Frequentist Bayes is objective (comment
                                  on articles by Berger and by Goldstein)  451--456
                   James Berger   Rejoinder  . . . . . . . . . . . . . . . 457--464
              Michael Goldstein   Subjectivity and objectivity in Bayesian
                                  statistics: rejoinder to the discussion  465--472
          William J. Browne and   
                   David Draper   A comparison of Bayesian and
                                  likelihood-based methods for fitting
                                  multilevel models  . . . . . . . . . . . 473--514
                  Andrew Gelman   Prior distributions for variance
                                  parameters in hierarchical models
                                  (comment on article by Browne and
                                  Draper)  . . . . . . . . . . . . . . . . 515--534
             Robert E. Kass and   
              Ranjini Natarajan   A default conjugate prior for variance
                                  components in generalized linear mixed
                                  models (comment on article by Browne and
                                  Draper)  . . . . . . . . . . . . . . . . 535--542
                Paul C. Lambert   (Comment on Article by Browne and
                                  Draper)  . . . . . . . . . . . . . . . . 543--546
          William J. Browne and   
                   David Draper   Rejoinder  . . . . . . . . . . . . . . . 547--550
              Ming-Hui Chen and   
              Joseph G. Ibrahim   The Relationship Between the Power Prior
                                  and Hierarchical Models  . . . . . . . . 551--574
              Timothy E. Hanson   Modeling Censored Lifetime Data Using a
                                  Mixture of Gammas Baseline . . . . . . . 575--594
          Margaret B. Short and   
              Bradley P. Carlin   Multivariate Spatiotemporal CDFs with
                                  Random Effects and Measurement Error . . 595--624
                    Bo Wang and   
             D. M. Titterington   Convergence properties of a general
                                  algorithm for calculating variational
                                  Bayesian estimates for a normal mixture
                                  model  . . . . . . . . . . . . . . . . . 625--650
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Bayesian Analysis
Volume 1, Number 4, December, 2006

                  G. Celeux and   
                  F. Forbes and   
               C. P. Robert and   
             D. M. Titterington   Deviance Information Criteria for
                                  Missing Data Models  . . . . . . . . . . 651--673
              Bradley P. Carlin   Comment on article by Celeux et al.  . . 675--676
                  Ming-Hui Chen   Comments on article by Celeux et al. . . 677--680
                 Martyn Plummer   Comment on article by Celeux et al.  . . 681--686
               Xiao-Li Meng and   
                   Florin Vaida   Comment on article by Celeux et al.  . . 687--698
         Angelika van der Linde   Comment on article by Celeux et al.  . . 699--700
                  G. Celeux and   
                  F. Forbes and   
               C. P. Robert and   
             D. M. Titterington   Rejoinder  . . . . . . . . . . . . . . . 701--705
           Paola Sebastiani and   
                    Hui Xie and   
                Marco F. Ramoni   Bayesian Analysis of Comparative
                                  Microarray Experiments by Model
                                  Averaging  . . . . . . . . . . . . . . . 707--732
                Fabio Rigat and   
          Mathisca de Gunst and   
                  Jaap van Pelt   Bayesian Modelling and Analysis of
                                  Spatio-Temporal Neuronal Networks  . . . 733--764
             Brian Williams and   
                Dave Higdon and   
               Jim Gattiker and   
               Leslie Moore and   
              Michael McKay and   
          Sallie Keller-McNulty   Combining Experimental Data and Computer
                                  Simulations, With an Application to
                                  Flyer Plate Experiments  . . . . . . . . 765--792
            Matthew J. Beal and   
              Zoubin Ghahramani   Variational Bayesian Learning of
                                  Directed Graphical Models with Hidden
                                  Variables  . . . . . . . . . . . . . . . 793--831
                  John Skilling   Nested Sampling for General Bayesian
                                  Computation  . . . . . . . . . . . . . . 833--859
      Jorge L. Bazán and   
           Marcia D. Branco and   
               Heleno Bolfarine   A Skew Item Response Model . . . . . . . 861--892
              Michael Evans and   
                 Hadas Moshonov   Checking for Prior-Data Conflict . . . . 893--914
               Rongheng Lin and   
            Thomas A. Louis and   
           Susan M. Paddock and   
                  Greg Ridgeway   Loss Function Based Ranking in
                                  Two-Stage, Hierarchical Models . . . . . 915--946
       Marco A. R. Ferreira and   
                  Mike West and   
          Herbert K. H. Lee and   
                David M. Higdon   Multi-Scale and Hidden Resolution Time
                                  Series Models  . . . . . . . . . . . . . 947--967
                Dale J. Poirier   The Growth of Bayesian Methods in
                                  Statistics and Economics Since 1970  . . 969--979
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Bayesian Analysis
Volume 2, Number 1, March, 2007

         Francesca Dominici and   
             Scott L. Zeger and   
        Giovanni Parmigiani and   
                Joanne Katz and   
                Parul Christian   Does the effect of micronutrient
                                  supplementation on neonatal survival
                                  vary with respect to the percentiles of
                                  the birth weight distribution? . . . . . 1--30
           Samantha R. Cook and   
            Elizabeth A. Stuart   Comment on article by Dominici et al.    31--35
              David Ruppert and   
             Raymond J. Carroll   Comment on article by Dominici et al.    37--42
         Francesca Dominici and   
             Scott L. Zeger and   
        Giovanni Parmigiani and   
                Joanne Katz and   
                Parul Christian   Rejoinder  . . . . . . . . . . . . . . . 43--44
    José M. Bernardo and   
            Sergio Pérez   Comparing Normal Means: New Methods for
                                  an Old Problem . . . . . . . . . . . . . 45--58
          Juan Antonio Cano and   
            Mathieu Kessler and   
          Diego Salmerón   Integral priors for the one way random
                                  effects model  . . . . . . . . . . . . . 59--67
         Carlos M. Carvalho and   
                      Mike West   Dynamic Matrix-Variate Graphical Models  69--97
              Robert Denham and   
               Kerrie Mengersen   Geographically Assisted Elicitation of
                                  Expert Opinion for Regression Models . . 99--135
               Dipak K. Dey and   
                    Junfeng Liu   A Quantitative Study of Quantile Based
                                  Direct Prior Elicitation from Expert
                                  Opinion  . . . . . . . . . . . . . . . . 137--166
                  Josep Ginebra   On the Measure of the Information in a
                                  Statistical Experiment . . . . . . . . . 167--211
           George Kokolakis and   
                George Kouvaras   On the Multimodality of Random
                                  Probability Measures . . . . . . . . . . 213--219
             Babak Shahbaba and   
                Radford M. Neal   Improving Classification When a Class
                                  Hierarchy is Available Using a
                                  Hierarchy-Based Prior  . . . . . . . . . 221--237
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Bayesian Analysis
Volume 2, Number 2, June, 2007

                     Kert Viele   Nonparametric Estimation of
                                  Kullback--Leibler Information
                                  Illustrated by Evaluating Goodness of
                                  Fit  . . . . . . . . . . . . . . . . . . 239--280
                  Haijun Ma and   
              Bradley P. Carlin   Bayesian Multivariate Areal Wombling for
                                  Multiple Disease Boundary Analysis . . . 281--302
             Carlos Almeida and   
                Michel Mouchart   Bayesian encompassing specification test
                                  under not completely known partial
                                  observability  . . . . . . . . . . . . . 303--318
         Angelika van der Linde   Local Influence on Posterior
                                  Distributions under Multiplicative Modes
                                  of Perturbation  . . . . . . . . . . . . 319--332
               R. G. Cowell and   
            S. L. Lauritzen and   
                     J. Mortera   A gamma model for DNA mixture analyses   333--348
          Josemar Rodrigues and   
               Heleno Bolfarine   Bayesian inference for an extended
                                  simple regression measurement error
                                  model using skewed priors  . . . . . . . 349--364
          Russell B. Millar and   
               Wayne S. Stewart   Assessment of Locally Influential
                                  Observations in Bayesian Models  . . . . 365--383
            S. Bhattacharya and   
                     J. Haslett   Importance Re-sampling MCMC for
                                  Cross-Validation in Inverse Problems . . 385--407
             E. C. Marshall and   
            D. J. Spiegelhalter   Identifying outliers in Bayesian
                                  hierarchical models: a simulation-based
                                  approach . . . . . . . . . . . . . . . . 409--444
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Bayesian Analysis
Volume 2, Number 3, September, 2007

                 Sonia Jain and   
                Radford M. Neal   Splitting and Merging Components of a
                                  Nonconjugate Dirichlet Process Mixture
                                  Model  . . . . . . . . . . . . . . . . . 445--472
                  David B. Dahl   Comment on article by Jain and Neal  . . 473--477
                   C. P. Robert   Comment on article by Jain and Neal  . . 479--482
           Steven N. MacEachern   Comment on article by Jain and Neal  . . 483--494
                 Sonia Jain and   
                Radford M. Neal   Rejoinder  . . . . . . . . . . . . . . . 495--500
               Eric P. Xing and   
                  Kyung-Ah Sohn   Hidden Markov Dirichlet Process:
                                  Modeling Genetic Inference in Open
                                  Ancestral Space  . . . . . . . . . . . . 501--527
                      Yi He and   
            James S. Hodges and   
              Bradley P. Carlin   Re-considering the variance
                                  parameterization in multiple precision
                                  models . . . . . . . . . . . . . . . . . 529--556
             Ana Maria Madrigal   Cluster Allocation Design Networks . . . 557--589
              Vanja Duki\'c and   
                   James Dignam   Bayesian Hierarchical Multiresolution
                                  Hazard Model for the Study of
                                  Time-Dependent Failure Patterns in Early
                                  Stage Breast Cancer  . . . . . . . . . . 591--609
                 Song Zhang and   
          Ya-Chen Tina Shih and   
              Peter Müller   A Spatially-adjusted Bayesian Additive
                                  Regression Tree Model to Merge Two
                                  Datasets . . . . . . . . . . . . . . . . 611--633
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Bayesian Analysis
Volume 2, Number 4, December, 2007

                  Marcus Hutter   Exact Bayesian Regression of Piecewise
                                  Constant Functions . . . . . . . . . . . 635--664
          Margaret B. Short and   
            David M. Higdon and   
            Philipp P. Kronberg   Estimation of Faraday Rotation Measures
                                  of the Near Galactic Sky Using Gaussian
                                  Process Models . . . . . . . . . . . . . 665--680
            Pierre Druilhet and   
              Jean-Michel Marin   Invariant HPD credible sets and MAP
                                  estimators . . . . . . . . . . . . . . . 681--691
          John Paul Gosling and   
           Jeremy E. Oakley and   
                Anthony O'Hagan   Nonparametric elicitation for
                                  heavy-tailed prior distributions . . . . 693--718
               Valen E. Johnson   Bayesian Model Assessment Using Pivotal
                                  Quantities . . . . . . . . . . . . . . . 719--733
                 Guofen Yan and   
                    J. Sedransk   Bayesian Diagnostic Techniques for
                                  Detecting Hierarchical Structure . . . . 735--760
       Jesper Mòller and   
               Kerrie Mengersen   Ergodic averages for monotone functions
                                  using upper and lower dominating
                                  processes  . . . . . . . . . . . . . . . 761--781
           Sourabh Bhattacharya   A Simulation Approach to Bayesian
                                  Emulation of Complex Dynamic Computer
                                  Models . . . . . . . . . . . . . . . . . 783--815
                 Mario Peruggia   Bayesian Model Diagnostics Based on
                                  Artificial Autoregressive Errors . . . . 817--841
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Bayesian Analysis
Volume 3, Number 1, March, 2008

         Bruno Sansó and   
            Chris E. Forest and   
             Daniel Zantedeschi   Inferring Climate System Properties
                                  Using a Computer Model . . . . . . . . . 1--37
                Dave Higdon and   
                 James Gattiker   Comment on article by Sansó et al.
                                  [MR2383247]  . . . . . . . . . . . . . . 39--44
               Jonathan Rougier   Comment on article by Sansó et al.
                                  [MR2383247]  . . . . . . . . . . . . . . 45--56
         Bruno Sansó and   
            Chris E. Forest and   
             Daniel Zantedeschi   Rejoinder  . . . . . . . . . . . . . . . 57--61
             Ivan Jeliazkov and   
                Dale J. Poirier   Dynamic and structural features of
                                  intifada violence: a Markov process
                                  approach . . . . . . . . . . . . . . . . 63--77
    Carlos A. de B. Pereira and   
        Julio Michael Stern and   
                Sergio Wechsler   Can a significance test be genuinely
                                  Bayesian?  . . . . . . . . . . . . . . . 79--100
            Peter McCullagh and   
                       Jie Yang   How many clusters? . . . . . . . . . . . 101--120
                Dan J. Spitzner   An asymptotic viewpoint on
                                  high-dimensional Bayesian testing  . . . 121--160
                   John Aldrich   R. A. Fisher on Bayes and Bayes' theorem 161--170
                 Longhai Li and   
              Jianguo Zhang and   
                Radford M. Neal   A method for avoiding bias from feature
                                  selection with application to naive
                                  Bayes classification models  . . . . . . 171--196
                 Sonali Das and   
              Ming-Hui Chen and   
                Sungduk Kim and   
                Nicholas Warren   A Bayesian Structural Equations Model
                                  for Multilevel Data with Missing
                                  Responses and Missing Covariates . . . . 197--224
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Bayesian Analysis
Volume 3, Number 2, June, 2008

            P. G. Blackwell and   
                     C. E. Buck   Estimating radiocarbon calibration
                                  curves . . . . . . . . . . . . . . . . . 225--248
               John Haslett and   
                 Andrew Parnell   Comment on article by Blackwell and Buck 249--254
              Andrew R. Millard   Comment on article by Blackwell and Buck 255--261
            P. G. Blackwell and   
                     C. E. Buck   Rejoinder  . . . . . . . . . . . . . . . 263--268
               Cyr E. M'Lan and   
            Lawrence Joseph and   
               David B. Wolfson   Bayesian Sample Size Determination for
                                  Binomial Proportions . . . . . . . . . . 269--296
José T. A. S. Ferreira and   
    Miguel A. Juárez and   
               Mark F. J. Steel   Directional log-spline distributions . . 297--316
       Fernando A. Quintana and   
          Peter Müller and   
             Gary L. Rosner and   
                   Mark Munsell   Semi-parametric Bayesian Inference for
                                  Multi-Season Baseball Data . . . . . . . 317--338
             Abel Rodriguez and   
              Enrique ter Horst   Bayesian dynamic density estimation  . . 339--365
                Jessica Tressou   Bayesian nonparametrics for heavy tailed
                                  distribution. Application to food risk
                                  assessment . . . . . . . . . . . . . . . 367--391
             Ivilina Popova and   
              Elmira Popova and   
               Edward I. George   Bayesian Forecasting of Prepayment Rates
                                  for Individual Pools of Mortgages  . . . 393--426
        Christian P. Robert and   
              Jean-Michel Marin   On some difficulties with a posterior
                                  probability approximation technique  . . 427--441
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Bayesian Analysis
Volume 3, Number 3, September, 2008

              Bradley P. Carlin   Editor in Chief's note . . . . . . . . . 443--444
                  Andrew Gelman   Objections to Bayesian statistics  . . . 445--449
        José M. Bernardo   Comment on article by Gelman . . . . . . 451--453
               Joseph B. Kadane   Comment on article by Gelman . . . . . . 455--457
                   Stephen Senn   Comment on article by Gelman . . . . . . 459--461
                Larry Wasserman   Comment on article by Gelman . . . . . . 463--465
                  Andrew Gelman   Rejoinder  . . . . . . . . . . . . . . . 467--477
                 Sam K. Hui and   
               Yanliu Huang and   
               Edward I. George   Model-based Analysis of Concept Maps . . 479--512
 Reinaldo B. Arellano-Valle and   
             Luis M. Castro and   
             Marc G. Genton and   
  Héctor W. Gómez   Bayesian inference for shape mixtures of
                                  skewed distributions, with application
                                  to regression analysis . . . . . . . . . 513--539
            Thomas J. Jiang and   
                James M. Dickey   Bayesian methods for categorical data
                                  under informative censoring  . . . . . . 541--553
      Simo Särkkä and   
                 Tommi Sottinen   Application of Girsanov Theorem to
                                  Particle Filtering of Discretely
                                  Observed Continuous-Time Non-Linear
                                  Systems  . . . . . . . . . . . . . . . . 555--584
              Ming-Hui Chen and   
                  Lan Huang and   
          Joseph G. Ibrahim and   
                    Sungduk Kim   Bayesian variable selection and
                                  computation for generalized linear
                                  models with conjugate priors . . . . . . 585--613
                Peter M. Hooper   Exact distribution theory for belief net
                                  responses  . . . . . . . . . . . . . . . 615--624
          Jarrett J. Barber and   
               Steven D. Prager   Combining multiple maps of line features
                                  to infer true position . . . . . . . . . 625--658
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Bayesian Analysis
Volume 3, Number 4, December, 2008

            Tobias Rydén   EM versus Markov chain Monte Carlo for
                                  estimation of hidden Markov models: a
                                  computational perspective  . . . . . . . 659--688
Sylvia Frühwirth-Schnatter   Comment on article by Rydén . . . . . . . 689--697
             Padhraic Smyth and   
                Sergey Kirshner   Comment on article by Rydén . . . . . . . 699--705
            Tobias Rydén   Rejoinder  . . . . . . . . . . . . . . . 707--715
               V. E. Rapley and   
                    A. H. Welsh   Model-based inferences from adaptive
                                  cluster sampling . . . . . . . . . . . . 717--736
              Damian Clancy and   
              Philip D. O'Neill   Bayesian estimation of the basic
                                  reproduction number in stochastic
                                  epidemic models  . . . . . . . . . . . . 737--757
     Hedibert Freitas Lopes and   
             Esther Salazar and   
                  Dani Gamerman   Spatial Dynamic Factor Analysis  . . . . 759--792
                 Longhai Li and   
                Radford M. Neal   Compressing parameters in Bayesian
                                  high-order models with application to
                                  logistic sequence models . . . . . . . . 793--821
        Alejandro Villagran and   
             Gabriel Huerta and   
         Charles S. Jackson and   
                  Mrinal K. Sen   Computational Methods for Parameter
                                  Estimation in Climate Models . . . . . . 823--850
 Vilda Purutçuo\uglu and   
                      Ernst Wit   Bayesian inference for the MAPK/ERK
                                  pathway by considering the dependency of
                                  the kinetic parameters . . . . . . . . . 851--886
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Bayesian Analysis
Volume 4, Number 1, March, 2009

         Peter F. Craigmile and   
        Catherine A. Calder and   
                 Hongfei Li and   
                 Rajib Paul and   
                   Noel Cressie   Hierarchical Model Building, Fitting,
                                  and Checking: A Behind-the-Scenes Look
                                  at a Bayesian Analysis of Arsenic
                                  Exposure Pathways  . . . . . . . . . . . 1--35
     Christopher David Barr and   
             Francesca Dominici   Comment on article by Craigmile et al.   37--39
                David B. Dunson   Comment on article by Craigmile et al.   41--43
           Alexandra M. Schmidt   Comment on article by Craigmile et al.   45--53
         Peter F. Craigmile and   
        Catherine A. Calder and   
                 Hongfei Li and   
                 Rajib Paul and   
                   Noel Cressie   Rejoinder  . . . . . . . . . . . . . . . 55--62
                Markus Hahn and   
                Jörn Sassy   Parameter estimation in continuous time
                                  Markov switching models: a
                                  semi-continuous Markov chain Monte Carlo
                                  approach . . . . . . . . . . . . . . . . 63--84
               R. B. O'Hara and   
      M. J. Sillanpää   A review of Bayesian variable selection
                                  methods: what, how and which . . . . . . 85--117
                     F. Liu and   
              M. J. Bayarri and   
                   J. O. Berger   Modularization in Bayesian Analysis,
                                  with Emphasis on Analysis of Computer
                                  Models . . . . . . . . . . . . . . . . . 119--150
                 Frank Tuyl and   
            Richard Gerlach and   
               Kerrie Mengersen   Posterior predictive arguments in favor
                                  of the Bayes--Laplace prior as the
                                  consensus prior for binomial and
                                  multinomial parameters . . . . . . . . . 151--158
                Scott Holan and   
             Tucker McElroy and   
             Sounak Chakraborty   A Bayesian Approach to Estimating the
                                  Long Memory Parameter  . . . . . . . . . 159--190
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Bayesian Analysis
Volume 4, Number 2, June, 2009

                   Guosheng Yin   Bayesian generalized method of moments   191--207
              Ming-Hui Chen and   
                    Sungduk Kim   Comments on article by Yin . . . . . . . 209--212
         Ciprian M. Crainiceanu   Comments on article by Yin . . . . . . . 213--215
                   Guosheng Yin   Rejoinder  . . . . . . . . . . . . . . . 217--222
   E. Gómez-Déniz   Some Bayesian credibility premiums
                                  obtained by using posterior regret $
                                  \Gamma $-minimax methodology . . . . . . 223--242
                  David B. Dahl   Modal clustering in a class of product
                                  partition models . . . . . . . . . . . . 243--264
      Isobel Claire Gormley and   
          Thomas Brendan Murphy   A grade of membership model for rank
                                  data . . . . . . . . . . . . . . . . . . 265--295
                 Chunlin Ji and   
                Daniel Merl and   
           Thomas B. Kepler and   
                      Mike West   Spatial mixture modelling for unobserved
                                  point processes: examples in
                                  immunofluorescence histology . . . . . . 297--315
               Aude Grelaud and   
        Christian P. Robert and   
          Jean-Michel Marin and   
   François Rodolphe and   
      Jean-François Taly   ABC likelihood-free methods for model
                                  choice in Gibbs random fields  . . . . . 317--335
             James S. Clark and   
              Michelle H. Hersh   Inference in incidence, infection, and
                                  impact: Co-infection of multiple hosts
                                  by multiple pathogens  . . . . . . . . . 337--365
               Arno Fritsch and   
                 Katja Ickstadt   Improved criteria for clustering based
                                  on the posterior similarity matrix . . . 367--391
                    Fei Liu and   
                      Mike West   A dynamic modelling strategy for
                                  Bayesian computer model emulation  . . . 393--411
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Bayesian Analysis
Volume 4, Number 3, September, 2009

              Stefano Monni and   
              Mahlet G. Tadesse   A stochastic partitioning method to
                                  associate high-dimensional responses and
                                  covariates . . . . . . . . . . . . . . . 413--436
               Hugh Chipman and   
              Edward George and   
               Robert McCulloch   Comment on article by Monni and Tadesse  437--438
                   Chris Fraley   Comment on article by Monni and Tadesse  439--447
                     Hongzhe Li   Comment on article by Monni and Tadesse  449--452
                      Hal Stern   Comment on article by Monni and Tadesse  453--456
              Stefano Monni and   
              Mahlet G. Tadesse   Rejoinder  . . . . . . . . . . . . . . . 457--464
            Chris P. Jewell and   
          Theodore Kypraios and   
                 Peter Neal and   
              Gareth O. Roberts   Bayesian analysis for emerging
                                  infectious diseases  . . . . . . . . . . 465--496
       Fernando A. Quintana and   
           Mark F. J. Steel and   
  José T. A. S. Ferreira   Flexible Univariate Continuous
                                  Distributions  . . . . . . . . . . . . . 497--521
             Julie Horrocks and   
     Marianne J. van Den Heuvel   Prediction of pregnancy: a joint model
                                  for longitudinal and binary data . . . . 523--538
            Silvia Liverani and   
           Paul E. Anderson and   
          Kieron D. Edwards and   
           Andrew J. Millar and   
                   Jim Q. Smith   Efficient Utility-based Clustering over
                                  High Dimensional Partition Spaces  . . . 539--571
            David S. Leslie and   
                Robert Kohn and   
               Denzil G. Fiebig   Nonparametric estimation of the
                                  distribution function in contingent
                                  valuation models . . . . . . . . . . . . 573--597
    Maurice J. Dupré and   
                Frank J. Tipler   New axioms for rigorous Bayesian
                                  probability  . . . . . . . . . . . . . . 599--606
         Melissa A. Bingham and   
        Stephen B. Vardeman and   
              Daniel J. Nordman   Bayes one-sample and one-way random
                                  effects analyses for $3$-D orientations
                                  with application to materials science    607--629
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Bayesian Analysis
Volume 4, Number 4, December, 2009

            Shane T. Jensen and   
        Blakeley B. McShane and   
               Abraham J. Wyner   Hierarchical Bayesian modeling of
                                  hitting performance in baseball  . . . . 631--652
                 Jim Albert and   
                  Phil Birnbaum   Comment on article by Jensen et al.  . . 653--660
               Mark E. Glickman   Comment on article by Jensen et al.  . . 661--664
       Fernando A. Quintana and   
              Peter Müller   Comment on article by Jensen et al.  . . 665--668
            Shane T. Jensen and   
        Blakeley B. McShane and   
               Abraham J. Wyner   Rejoinder  . . . . . . . . . . . . . . . 669--674
              Minjung Kyung and   
                 Sujit K. Ghosh   Bayesian Inference for Directional
                                  Conditionally Autoregressive Models  . . 675--706
                  Sinae Kim and   
              David B. Dahl and   
                Marina Vannucci   Spiked Dirichlet Process Prior for
                                  Bayesian Multiple Hypothesis Testing in
                                  Random Effects Models  . . . . . . . . . 707--732
              Jason A. Duan and   
            Alan E. Gelfand and   
                  C. F. Sirmans   Modeling space-time data using
                                  stochastic differential equations  . . . 733--758
             Ronald Christensen   Inconsistent Bayesian estimation . . . . 759--762
              Hongmei Zhang and   
                      Hal Stern   Sample Size Calculation for Finding
                                  Unseen Species . . . . . . . . . . . . . 763--792
           Matthew A. Taddy and   
              Athanasios Kottas   Markov Switching Dirichlet Process
                                  Mixture Regression . . . . . . . . . . . 793--816
    Jairo A. Fúquene and   
               John D. Cook and   
               Luis R. Pericchi   A Case for Robust Bayesian Priors with
                                  Applications to Clinical Trials  . . . . 817--846
              Bradley P. Carlin   Editor-in-chief's note . . . . . . . . . 847--850
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Bayesian Analysis
Volume 5, Number 1, March, 2010

            Charles R. Hogg and   
           Joseph B. Kadane and   
               Jong Soo Lee and   
               Sara A. Majetich   Error analysis for small angle neutron
                                  scattering datasets using Bayesian
                                  inference  . . . . . . . . . . . . . . . 1--33
                Nick Hengartner   Comment on article by Hogg et al.  . . . 35--37
              John Skilling and   
                 Devinder Sivia   Comment on article by Hogg et al.  . . . 39--40
            Charles R. Hogg and   
           Joseph B. Kadane and   
               Jong Soo Lee and   
               Sara A. Majetich   Rejoinder  . . . . . . . . . . . . . . . 41--43
                  J. E. Griffin   Default priors for density estimation
                                  with mixture models  . . . . . . . . . . 45--64
              Tomohiro Ando and   
                 Arnold Zellner   Hierarchical Bayesian analysis of the
                                  seemingly unrelated regression and
                                  simultaneous equations models using a
                                  combination of direct Monte Carlo and
                                  importance sampling techniques . . . . . 65--95
        Avishek Chakraborty and   
                Alan E. Gelfand   Analyzing spatial point patterns subject
                                  to measurement error . . . . . . . . . . 97--122
            Cari G. Kaufman and   
                Stephan R. Sain   Bayesian functional ANOVA modeling using
                                  Gaussian process prior distributions . . 123--149
                    Qing Li and   
                        Nan Lin   The Bayesian elastic net . . . . . . . . 151--170
             Jim E. Griffin and   
                Philip J. Brown   Inference with normal-gamma prior
                                  distributions in regression problems . . 171--188
               Xiaoxi Zhang and   
         Timothy D. Johnson and   
      Roderick J. A. Little and   
                        Yue Cao   A Bayesian Image Analysis of Radiation
                                  Induced Changes in Tumor Vascular
                                  Permeability . . . . . . . . . . . . . . 189--212
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Bayesian Analysis
Volume 5, Number 2, June, 2010

            Christian P. Robert   The search for certainty: a critical
                                  assessment . . . . . . . . . . . . . . . 213--222
                Larry Wasserman   Comment on Article by Robert . . . . . . 223--228
                  Andrew Gelman   Comment on Article by Robert . . . . . . 229--232
               Krzysztof Burdzy   Comment on Article by Robert . . . . . . 233--236
          Robert B. Gramacy and   
                 Ester Pantaleo   Shrinkage regression for multivariate
                                  inference with missing data, and an
                                  application to portfolio balancing . . . 237--262
  J. Andrés Christen and   
                      Colin Fox   A general purpose sampling algorithm for
                                  continuous distributions (the $t$-walk)  263--281
                Bertrand Clarke   Desiderata for a predictive theory of
                                  statistics . . . . . . . . . . . . . . . 283--318
            Surya T. Tokdar and   
                  Yu M. Zhu and   
               Jayanta K. Ghosh   Bayesian Density Regression with
                                  Logistic Gaussian Process and Subspace
                                  Projection . . . . . . . . . . . . . . . 319--344
        Christoph Pamminger and   
Sylvia Frühwirth-Schnatter   Model-based Clustering of Categorical
                                  Time Series  . . . . . . . . . . . . . . 345--368
              Minjung Kyung and   
                  Jeff Gill and   
                Malay Ghosh and   
                 George Casella   Penalized Regression, Standard Errors,
                                  and Bayesian Lassos  . . . . . . . . . . 369--411
                   Jing Cao and   
                     Song Zhang   Measuring statistical significance for
                                  full Bayesian methods in microarray
                                  analyses . . . . . . . . . . . . . . . . 413--427
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Bayesian Analysis
Volume 5, Number 3, September, 2010

        Ioanna Manolopoulou and   
               Cliburn Chan and   
                      Mike West   Selection Sampling from Large Data Sets
                                  for Targeted Inference in Mixture
                                  Modeling . . . . . . . . . . . . . . . . 429--449
                    Fabio Rigat   Comment on article by Manolopoulou et
                                  al.  . . . . . . . . . . . . . . . . . . 451--455
                  Nick Whiteley   Comment on article by Manolopoulou et
                                  al.  . . . . . . . . . . . . . . . . . . 457--460
        Ioanna Manolopoulou and   
               Cliburn Chan and   
                      Mike West   Rejoinder  . . . . . . . . . . . . . . . 461--463
           Gareth W. Peters and   
        Balakrishnan Kannan and   
               Ben Lasscock and   
                   Chris Mellen   Model Selection and Adaptive Markov
                                  chain Monte Carlo for Bayesian
                                  Cointegrated VAR Models  . . . . . . . . 465--491
       Anandamayee Majumdar and   
              Debashis Paul and   
                     Jason Kaye   Sensitivity analysis and model selection
                                  for a generalized convolution model for
                                  spatial processes  . . . . . . . . . . . 493--518
     Jules J. S. de Tibeiro and   
              Duncan J. Murdoch   Correspondence Analysis with Incomplete
                                  Paired Data using Bayesian Imputation    519--532
                    Qing Li and   
                  Ruibin Xi and   
                        Nan Lin   Bayesian regularized quantile regression 533--556
             Margaret Short and   
                Dave Higdon and   
           Laura Guadagnini and   
         Alberto Guadagnini and   
          Daniel M. Tartakovsky   Predicting Vertical Connectivity Within
                                  an Aquifer System  . . . . . . . . . . . 557--581
            Leonard Bottolo and   
              Sylvia Richardson   Evolutionary stochastic search for
                                  Bayesian model exploration . . . . . . . 583--618
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Bayesian Analysis
Volume 5, Number 4, December, 2010

                 Ian Vernon and   
          Michael Goldstein and   
               Richard G. Bower   Galaxy Formation: a Bayesian Uncertainty
                                  Analysis . . . . . . . . . . . . . . . . 619--669
                    David Poole   Comment on article by Vernon et al.  . . 671--675
                  Pritam Ranjan   Comment on article by Vernon et al.  . . 677--681
              Earl Lawrence and   
                David M. Higdon   Comment on Article by Vernon et al.  . . 683--689
               David A. van Dyk   Comment on article by Vernon et al.  . . 691--695
                 Ian Vernon and   
          Michael Goldstein and   
               Richard G. Bower   Rejoinder  . . . . . . . . . . . . . . . 697--708
         Carlos M. Carvalho and   
          Hedibert F. Lopes and   
         Nicholas G. Polson and   
                  Matt A. Taddy   Particle learning for general mixtures   709--740
                   Ruby C. Weng   A Bayesian Edgeworth expansion by
                                  Stein's identity . . . . . . . . . . . . 741--763
             Kathryn Barger and   
                     John Bunge   Objective Bayesian estimation for the
                                  number of species  . . . . . . . . . . . 765--785
            S. A. Kharroubi and   
                 T. J. Sweeting   Posterior simulation via the signed root
                                  log-likelihood ratio . . . . . . . . . . 787--815
                XuanLong Nguyen   Inference of global clusters from
                                  locally distributed data . . . . . . . . 817--845
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Bayesian Analysis
Volume 6, Number 1, March, 2011

         Nicholas G. Polson and   
                Steven L. Scott   Data augmentation for support vector
                                  machines . . . . . . . . . . . . . . . . 1--23
            Bani K. Mallick and   
         Sounak Chakraborty and   
                    Malay Ghosh   Comment on article by Polson and Scott   25--29
             Babak Shahbaba and   
                  Yaming Yu and   
               David A. van Dyk   Comment on article by Polson and Scott   31--35
                     Chris Hans   Comment on article by Polson and Scott   37--41
         Nicholas G. Polson and   
                Steven L. Scott   Rejoinder: ``Data augmentation for
                                  support vector machines''  . . . . . . . 43--47
             Xavier Didelot and   
         Richard G. Everitt and   
           Adam M. Johansen and   
               Daniel J. Lawson   Likelihood-free estimation of model
                                  evidence . . . . . . . . . . . . . . . . 49--76
         Angelika van der Linde   Reduced rank regression models with
                                  latent variables in Bayesian functional
                                  data analysis  . . . . . . . . . . . . . 77--126
Amélie Crépet and   
                Jessica Tressou   Bayesian nonparametric model for
                                  clustering individual co-exposure to
                                  pesticides found in the French diet  . . 127--144
      Abel Rodríguez and   
                David B. Dunson   Nonparametric Bayesian models through
                                  probit stick-breaking processes  . . . . 145--177
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Bayesian Analysis
Volume 6, Number 2, June, 2011

                  Peter D. Hoff   Separable covariance arrays via the
                                  Tucker product, with applications to
                                  multivariate relational data . . . . . . 179--196
              Genevera I. Allen   Comment on article by Hoff . . . . . . . 197--201
         Hedibert Freitas Lopes   Comment on article by Hoff . . . . . . . 203--204
                  Peter D. Hoff   Rejoinder: ``Comment on article by
                                  Hoff'' . . . . . . . . . . . . . . . . . 205--207
                 Meli Baragatti   Bayesian variable selection for probit
                                  mixed models applied to gene selection   209--229
              Osnat Stramer and   
                 Matthew Bognar   Bayesian inference for irreducible
                                  diffusion processes using the
                                  pseudo-marginal approach . . . . . . . . 231--258
           Ma\lgorzata Roos and   
                  Leonhard Held   Sensitivity analysis in Bayesian
                                  generalized linear mixed models for
                                  binary data  . . . . . . . . . . . . . . 259--278
                Guy Freeman and   
                   Jim Q. Smith   Dynamic staged trees for discrete
                                  multivariate time series: forecasting,
                                  model selection and causal analysis  . . 279--305
                 James G. Scott   Bayesian estimation of intensity
                                  surfaces on the sphere via needlet
                                  shrinkage and selection  . . . . . . . . 307--327
            Christopher Yau and   
                   Chris Holmes   Hierarchical Bayesian nonparametric
                                  mixture models for clustering with
                                  variable relevance determination . . . . 329--351
              Ralf van der Lans   Bayesian estimation of the multinomial
                                  logit model: a comment on Holmes and
                                  Held, ``Bayesian auxiliary variable
                                  models for binary and multinomial
                                  regression'' . . . . . . . . . . . . . . 353--355
               Chris Holmes and   
                  Leonhard Held   Response to van der Lans . . . . . . . . 357--358
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Bayesian Analysis
Volume 6, Number 3, September, 2011

                  Sara Wade and   
         Silvia Mongelluzzo and   
                  Sonia Petrone   An enriched conjugate prior for Bayesian
                                  nonparametric inference  . . . . . . . . 359--385
Daniel Sabanés Bové and   
                  Leonhard Held   Hyper-$g$ Priors for Generalized Linear
                                  Models . . . . . . . . . . . . . . . . . 387--410
              Laura Ventura and   
                 Walter Racugno   Recent advances on Bayesian inference
                                  for $ P(X < Y) $  . . . . . . . . . . . . 411--428
             Stefano Cabras and   
María Eugenia Castellanos and   
           Alicia Quirós   Goodness-of-fit of conditional
                                  regression models for multiple
                                  imputation . . . . . . . . . . . . . . . 429--455
             Maarten Blaauw and   
      J. Andrés Christen   Flexible paleoclimate age-depth models
                                  using an autoregressive gamma process    457--474
               Eric B. Ford and   
         Althea V. Moorhead and   
                  Dimitri Veras   A Bayesian surrogate model for rapid
                                  time series analysis and application to
                                  exoplanet observations . . . . . . . . . 475--499
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Bayesian Analysis
Volume 6, Number 4, December, 2011

                 Jason Wyse and   
                 Nial Friel and   
               Håvard Rue   Approximate simulation-free Bayesian
                                  inference for multiple changepoint
                                  models with dependence within segments   501--528
                 Paul Fearnhead   Comment on Article by Wyse et al.  . . . 529--532
                      Gary Koop   Comment on Article by Wyse et al.  . . . 533--540
                 Jason Wyse and   
                 Nial Friel and   
               Håvard Rue   Rejoinder: ``Comment on Article by Wyse
                                  et al.'' . . . . . . . . . . . . . . . . 541--546
            Surya T. Tokdar and   
             Iris Grossmann and   
           Joseph B. Kadane and   
        Anne-Sophie Charest and   
              Mitchell J. Small   Impact of Beliefs About Atlantic
                                  Tropical Cyclone Detection on
                                  Conclusions About Trends in Tropical
                                  Cyclone Numbers  . . . . . . . . . . . . 547--572
                  Cinzia Viroli   Model based clustering for three-way
                                  data structures  . . . . . . . . . . . . 573--602
                Dan J. Spitzner   Neutral-data comparisons for Bayesian
                                  testing  . . . . . . . . . . . . . . . . 603--638
                   Hao Wang and   
               Craig Reeson and   
             Carlos M. Carvalho   Dynamic Financial Index Models: Modeling
                                  Conditional Dependencies via Graphs  . . 639--664
        Matthew S. Shotwell and   
             Elizabeth H. Slate   Bayesian Outlier Detection with
                                  Dirichlet Process Mixtures . . . . . . . 665--690
 João V. D. Monteiro and   
Renato M. Assunção and   
            Rosangela H. Loschi   Product partition models with correlated
                                  parameters . . . . . . . . . . . . . . . 691--726
                  David Leonard   Estimating a bivariate linear
                                  relationship . . . . . . . . . . . . . . 727--754
           Gareth W. Peters and   
        Balakrishnan Kannan and   
               Ben Lasscock and   
               Chris Mellen and   
                  Simon Godsill   Bayesian Cointegrated Vector
                                  Autoregression Models Incorporating
                                  alpha-stable Noise for Inter-day Price
                                  Movements Via Approximate Bayesian
                                  Computation  . . . . . . . . . . . . . . 755--792
                  Minjung Kyung   A Computational Bayesian Method for
                                  Estimating the Number of Knots In
                                  Regression Splines . . . . . . . . . . . 793--828
                 Luke Bornn and   
          François Caron   Bayesian clustering in decomposable
                                  graphs . . . . . . . . . . . . . . . . . 829--846
            Matthew P. Wand and   
            John T. Ormerod and   
           Simone A. Padoan and   
         Rudolf Frührwirth   Mean Field Variational Bayes for
                                  Elaborate Distributions  . . . . . . . . 847--900
      Eleni-Ioanna Delatola and   
                 Jim E. Griffin   Bayesian Nonparametric Modelling of the
                                  Return Distribution with Stochastic
                                  Volatility . . . . . . . . . . . . . . . 901--926
                      Anonymous   Supplemental file  . . . . . . . . . . . ??
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Bayesian Analysis
Volume 7, Number 1, March, 2012

               Alessio Sancetta   Universality of Bayesian Predictions . . 1--36
                Bertrand Clarke   Comment on Article by Sancetta . . . . . 37--44
                     Feng Liang   Comment on Article by Sancetta . . . . . 45--46
               Alessio Sancetta   Rejoinder  . . . . . . . . . . . . . . . 47--50
            Surya T. Tokdar and   
               Joseph B. Kadane   Simultaneous Linear Quantile Regression:
                                  A Semiparametric Bayesian Approach . . . 51--72
           Peter Carbonetto and   
               Matthew Stephens   Scalable Variational Inference for
                                  Bayesian Variable Selection in
                                  Regression, and Its Accuracy in Genetic
                                  Association Studies  . . . . . . . . . . 73--108
              Alexina Mason and   
          Sylvia Richardson and   
                     Nicky Best   Two-Pronged Strategy for Using DIC to
                                  Compare Selection Models with
                                  Non-Ignorable Missing Responses  . . . . 109--146
          Timothy E. Hanson and   
             Alejandro Jara and   
                    Luping Zhao   A Bayesian Semiparametric
                                  Temporally-Stratified Proportional
                                  Hazards Model with Spatial Frailties . . 147--188
              Yangxin Huang and   
              Getachew A. Dagne   Simultaneous Bayesian Inference for
                                  Skew-Normal Semiparametric Nonlinear
                                  Mixed-Effects Models with Covariate
                                  Measurement Errors . . . . . . . . . . . 189--210
        Camila C. S. Caiado and   
           Richard W. Hobbs and   
              Michael Goldstein   Bayesian Strategies to Assess
                                  Uncertainty in Velocity Models . . . . . 211--234
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Bayesian Analysis
Volume 7, Number 2, June, 2012

               Kristian Lum and   
                Alan E. Gelfand   Spatial Quantile Multiple Regression
                                  Using the Asymmetric Laplace Process . . 235--258
        Rajarshi Guhaniyogi and   
               Sudipto Banerjee   Comment on Article by Lum and Gelfand    259--262
                    Nan Lin and   
                     Chao Chang   Comment on Article by Lum and Gelfand    263--270
           Marco A. R. Ferreira   Comment on Article by Lum and Gelfand    271--272
               Kristian Lum and   
                Alan E. Gelfand   Rejoinder  . . . . . . . . . . . . . . . 273--276
Andrés F. Barrientos and   
             Alejandro Jara and   
           Fernando A. Quintana   On the Support of MacEachern's Dependent
                                  Dirichlet Processes and Extensions . . . 277--310
          Vincent Rivoirard and   
                Judith Rousseau   Posterior Concentration Rates for
                                  Infinite Dimensional Exponential
                                  Families . . . . . . . . . . . . . . . . 311--334
           Matthew A. Taddy and   
              Athanasios Kottas   Mixture Modeling for Marked Poisson
                                  Processes  . . . . . . . . . . . . . . . 335--362
               Serena Arima and   
             Gauri S. Datta and   
                  Brunero Liseo   Objective Bayesian Analysis of a
                                  Measurement Error Small Area Model . . . 363--384
            Roberto Casarin and   
        Luciana Dalla Valle and   
                Fabrizio Leisen   Bayesian Model Selection for Beta
                                  Autoregressive Processes . . . . . . . . 385--410
                 M. J. Rufo and   
           J. Martín and   
             C. J. Pérez   Log-Linear Pool to Combine Prior
                                  Distributions: A Suggestion for a
                                  Calibration-Based Approach . . . . . . . 411--438
           Tamara Broderick and   
          Michael I. Jordan and   
                     Jim Pitman   Beta Processes, Stick-Breaking, and
                                  Power Laws . . . . . . . . . . . . . . . 439--476
              Gilles Celeux and   
         Mohammed El Anbari and   
          Jean-Michel Marin and   
            Christian P. Robert   Regularization in Regression: Comparing
                                  Bayesian and Frequentist Methods in a
                                  Poorly Informative Situation . . . . . . 477--502
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
                      Anonymous   Whole issue  . . . . . . . . . . . . . . ??

Bayesian Analysis
Volume 7, Number 3, September, 2012

            Isabelle Albert and   
              Sophie Donnet and   
 Chantal Guihenneuc-Jouyaux and   
          Samantha Low-Choy and   
           Kerrie Mengersen and   
                Judith Rousseau   Combining Expert Opinions in Prior
                                  Elicitation  . . . . . . . . . . . . . . 503--532
                   Simon French   Comment on Article by Albert et al.  . . 533--536
              John Paul Gosling   Comment on Article by Albert et al.  . . 537--540
            Isabelle Albert and   
              Sophie Donnet and   
 Chantal Guihenneuc-Jouyaux and   
          Samantha Low-Choy and   
           Kerrie Mengersen and   
                Judith Rousseau   Rejoinder  . . . . . . . . . . . . . . . 541--546
                 Kim Kenobi and   
                  Ian L. Dryden   Bayesian Matching of Unlabeled Point
                                  Sets Using Procrustes and Configuration
                                  Models . . . . . . . . . . . . . . . . . 547--566
          Robert B. Gramacy and   
             Nicholas G. Polson   Simulation-based Regularized Logistic
                                  Regression . . . . . . . . . . . . . . . 567--590
             Satoshi Morita and   
             Peter F. Thall and   
              Peter Müller   Prior Effective Sample Size in
                                  Conditionally Independent Hierarchical
                                  Models . . . . . . . . . . . . . . . . . 591--614
                Irene Vrbik and   
                Rob Deardon and   
                  Zeny Feng and   
              Abbie Gardner and   
                     John Braun   Using Individual-Level Models for
                                  Infectious Disease Spread to Model
                                  Spatio-Temporal Combustion Dynamics  . . 615--638
             Brian P. Hobbs and   
          Daniel J. Sargent and   
              Bradley P. Carlin   Commensurate Priors for Incorporating
                                  Historical Information in Clinical
                                  Trials Using General and Generalized
                                  Linear Models  . . . . . . . . . . . . . 639--674
    Sabyasachi Mukhopadhyay and   
           Sourabh Bhattacharya   Perfect Simulation for Mixtures with
                                  Known and Unknown Number of Components   675--714
              Antti Solonen and   
            Pirkka Ollinaho and   
                Marko Laine and   
              Heikki Haario and   
           Johanna Tamminen and   
           Heikki Järvinen   Efficient MCMC for Climate Model
                                  Parameter Estimation: Parallel Adaptive
                                  Chains and Early Rejection . . . . . . . 715--736
             Martin D. Weinberg   Computing the Bayes Factor from a Markov
                                  Chain Monte Carlo Simulation of the
                                  Posterior Distribution . . . . . . . . . 737--770
                      Anonymous   Supplemental file  . . . . . . . . . . . ??
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
                      Anonymous   Whole issue  . . . . . . . . . . . . . . ??

Bayesian Analysis
Volume 7, Number 4, December, 2012

                Sungduk Kim and   
        Rajeshwari Sundaram and   
     Germaine M. Buck Louis and   
                  Cecilia Pyper   Flexible Bayesian Human Fecundity Models 771--800
                   Bruno Scarpa   Comment on Article by Kim et al. . . . . 801--804
             Joseph B. Stanford   Comment on Article by Kim et al. . . . . 805--808
                Sungduk Kim and   
        Rajeshwari Sundaram and   
     Germaine M. Buck Louis and   
                  Cecilia Pyper   Rejoinder  . . . . . . . . . . . . . . . 809--812
               Mingtao Ding and   
                   Lihan He and   
               David Dunson and   
                 Lawrence Carin   Nonparametric Bayesian Segmentation of a
                                  Multivariate Inhomogeneous Space-Time
                                  Poisson Process  . . . . . . . . . . . . 813--840
          Cristian L. Bayes and   
      Jorge L. Bazán and   
         Catalina García   A New Robust Regression Model for
                                  Proportions  . . . . . . . . . . . . . . 841--866
                       Hao Wang   Bayesian Graphical Lasso Models and
                                  Efficient Posterior Computation  . . . . 867--886
         Nicholas G. Polson and   
                 James G. Scott   On the Half-Cauchy Prior for a Global
                                  Scale Parameter  . . . . . . . . . . . . 887--902
            Pierre Druilhet and   
                 Denys Pommeret   Invariant Conjugate Analysis for
                                  Exponential Families . . . . . . . . . . 903--916
              Joungyoun Kim and   
          Nicola M. Anthony and   
                 Bret R. Larget   A Bayesian Method for Estimating
                                  Evolutionary History . . . . . . . . . . 917--974
             Enrico Fabrizi and   
                Carlo Trivisano   Bayesian Estimation of Log-Normal Means
                                  with Finite Quadratic Expected Loss  . . 975--996
               John Paisley and   
                 Chong Wang and   
                  David M. Blei   The Discrete Infinite Logistic Normal
                                  Distribution . . . . . . . . . . . . . . 997--1034
                    Lin Huo and   
                  Ying Yuan and   
                   Guosheng Yin   Bayesian Dose Finding for Combined Drugs
                                  with Discrete and Continuous Doses . . . 1035--1052
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
                      Anonymous   Whole issue  . . . . . . . . . . . . . . ??


Bayesian Analysis
Volume 8, Number 1, March, 2013

             Daniel Schmidl and   
              Claudia Czado and   
                 Sabine Hug and   
                Fabian J. Theis   A Vine-copula Based Adaptive MCMC
                                  Sampler for Efficient Inference of
                                  Dynamical Systems  . . . . . . . . . . . 1--22
                Dawn B. Woodard   Comment on Article by Schmidl et al. . . 23--26
              Mark Girolami and   
                Antonietta Mira   Comment on Article by Schmidl et al. . . 27--32
             Daniel Schmidl and   
              Claudia Czado and   
                 Sabine Hug and   
                Fabian J. Theis   Rejoinder  . . . . . . . . . . . . . . . 33--42
         Francisco J. Rubio and   
               Mark F. J. Steel   Bayesian Inference for $ P(X < Y) $ Using
                                  Asymmetric Dependent Distributions . . . 43--62
        Maria Anna Di Lucca and   
       Alessandra Guglielmi and   
          Peter Müller and   
           Fernando A. Quintana   A Simple Class of Bayesian Nonparametric
                                  Autoregression Models  . . . . . . . . . 63--88
              Charles Geyer and   
                    Glen Meeden   Asymptotics for Constrained Dirichlet
                                  Distributions  . . . . . . . . . . . . . 89--110
            Jyotishka Datta and   
               Jayanta K. Ghosh   Asymptotic Properties of Bayes Risk for
                                  the Horseshoe Prior  . . . . . . . . . . 111--132
                 Kiona Ogle and   
             Jarrett Barber and   
                   Karla Sartor   Feedback and Modularization in a
                                  Bayesian Meta--analysis of Tree Traits
                                  Affecting Forest Dynamics  . . . . . . . 133--168
          John Paul Gosling and   
                  Andy Hart and   
                 Helen Owen and   
             Michael Davies and   
                     Jin Li and   
                 Cameron MacKay   A Bayes Linear Approach to
                                  Weight-of-Evidence Risk Assessment for
                                  Skin Allergy . . . . . . . . . . . . . . 169--186
          Alain Desgagné   Full Robustness in Bayesian Modelling of
                                  a Scale Parameter  . . . . . . . . . . . 187--220
            Morris L. Eaton and   
           Robb J. Muirhead and   
                Adina I. Soaita   On the Limiting Behavior of the
                                  ``Probability of Claiming Superiority''
                                  in a Bayesian Context  . . . . . . . . . 221--232
                  Eric Wang and   
             Esther Salazar and   
               David Dunson and   
                 Lawrence Carin   Spatio-Temporal Modeling of Legislation
                                  and Votes  . . . . . . . . . . . . . . . 233--268
                      Anonymous   Supplemental file  . . . . . . . . . . . ??
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
                      Anonymous   Whole issue  . . . . . . . . . . . . . . ??

Bayesian Analysis
Volume 8, Number 2, June, 2013

          Peter Müller and   
                    Riten Mitra   Bayesian Nonparametric Inference -- Why
                                  and How  . . . . . . . . . . . . . . . . 269--302
          Bradley P. Carlin and   
               Thomas A. Murray   Comment on Article by Müller and Mitra    303--310
                  Peter D. Hoff   Comment on Article by Müller and Mitra    311--318
                Anthony O'Hagan   Comment on Article by Müller and Mitra    319--322
              Murray Aitken and   
                Julia Polak and   
               Julyan Arbel and   
            Bernardo Nipoti and   
         Bertrand S. Clarke and   
            Gregory E. Holt and   
              Andrew Gelman and   
Miroslav Kárný and   
       Michalis Kolossiatis and   
          Athanasios Kottas and   
              Maria DeYoreo and   
             Valerie Poynor and   
           Susan M. Paddock and   
       Terrance D. Savitsky and   
              G. Parmigiani and   
                  L. Trippa and   
     François Perron and   
        Christian P. Robert and   
            Judith Rousseau and   
             James G. Scott and   
                Surya T. Tokdar   Contributed Discussion on Article by
                                  Müller and Mitra  . . . . . . . . . . . . 323--356
          Peter Müller and   
                    Riten Mitra   Rejoinder  . . . . . . . . . . . . . . . 357--360
          Juan Antonio Cano and   
          Diego Salmerón   Integral Priors and Constrained
                                  Imaginary Training Samples for Nested
                                  and Non-nested Bayesian Model Comparison 361--380
        Cristiano C. Santos and   
        Rosangela H. Loschi and   
     Reinaldo B. Arellano-Valle   Parameter Interpretation in Skewed
                                  Logistic Regression with Random
                                  Intercept  . . . . . . . . . . . . . . . 381--410
             Paul Fearnhead and   
             Benjamin M. Taylor   An Adaptive Sequential Monte Carlo
                                  Sampler  . . . . . . . . . . . . . . . . 411--438
                 Alan Huang and   
                     M. P. Wand   Simple Marginally Noninformative Prior
                                  Distributions for Covariance Matrices    439--452
           Lane F. Burgette and   
               Jerome P. Reiter   Multiple-Shrinkage Multinomial Probit
                                  Models with Applications to Simulating
                                  Geographies in Public Use Data . . . . . 453--478
             Karthik Sriram and   
          R. V. Ramamoorthi and   
                    Pulak Ghosh   Posterior Consistency of Bayesian
                                  Quantile Regression Based on the
                                  Misspecified Asymmetric Laplace Density  479--504
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
                      Anonymous   Whole issue  . . . . . . . . . . . . . . ??

Bayesian Analysis
Volume 8, Number 3, September, 2013

                  Marco Scutari   On the Prior and Posterior Distributions
                                  Used in Graphical Modelling  . . . . . . 505--532
                   Adrian Dobra   Comment on Article by Scutari  . . . . . 533--538
      Christine B. Peterson and   
            Francesco C. Stingo   Comment on Article by Scutari  . . . . . 539--542
                       Hao Wang   Comment on Article by Scutari  . . . . . 543--548
                  Marco Scutari   Rejoinder  . . . . . . . . . . . . . . . 549--552
             Luai Al Labadi and   
               Mahmoud Zarepour   On Asymptotic Properties and Almost Sure
                                  Approximation of the Normalized
                                  Inverse-Gaussian Process . . . . . . . . 553--568
             Zeynep Baskurt and   
                  Michael Evans   Hypothesis Assessment and Inequalities
                                  for Bayes Factors and Relative Belief
                                  Ratios . . . . . . . . . . . . . . . . . 569--590
             John R. Bryant and   
              Patrick J. Graham   Bayesian Demographic Accounts:
                                  Subnational Population Estimation Using
                                  Multiple Data Sources  . . . . . . . . . 591--622
Vanda Inácio de Carvalho and   
             Alejandro Jara and   
          Timothy E. Hanson and   
             Miguel de Carvalho   Bayesian Nonparametric ROC Regression
                                  Modeling . . . . . . . . . . . . . . . . 623--646
       Jennifer Lynn Clarke and   
            Bertrand Clarke and   
                     Chi-Wai Yu   Prediction in $ \mathcal {M}$-complete
                                  Problems with Limited Sample Size  . . . 647--690
             Jim E. Griffin and   
                Philip J. Brown   Some Priors for Sparse Regression
                                  Modelling  . . . . . . . . . . . . . . . 691--702
                   Suyu Liu and   
                      Jing Ning   A Bayesian Dose-finding Design for Drug
                                  Combination Trials with Delayed
                                  Toxicities . . . . . . . . . . . . . . . 703--722
                    A. Jara and   
        L. E. Nieto-Barajas and   
                    F. Quintana   A Time Series Model for Responses on the
                                  Unit Interval  . . . . . . . . . . . . . 723--740
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
                      Anonymous   Whole issue  . . . . . . . . . . . . . . ??

Bayesian Analysis
Volume 8, Number 4, December, 2013

               Valen E. Johnson   On Numerical Aspects of Bayesian Model
                                  Selection in High and
                                  Ultrahigh-dimensional Settings . . . . . 741--758
                  Yanxun Xu and   
                  Juhee Lee and   
                  Yuan Yuan and   
                Riten Mitra and   
              Shoudan Liang and   
          Peter Müller and   
                        Yuan Ji   Nonparametric Bayesian Bi-Clustering for
                                  Next Generation Sequencing Count Data    759--780
         Pierpaolo De Blasi and   
              Stephen G. Walker   Bayesian Estimation of the Discrepancy
                                  with Misspecified Parametric Models  . . 781--800
           Tamara Broderick and   
                 Jim Pitman and   
              Michael I. Jordan   Feature Allocations, Probability
                                  Functions, and Paintboxes  . . . . . . . 801--836
               Tim Salimans and   
               David A. Knowles   Fixed-Form Variational Posterior
                                  Approximation through Stochastic Linear
                                  Regression . . . . . . . . . . . . . . . 837--882
                Qingzhao Yu and   
       Steven N. MacEachern and   
                 Mario Peruggia   Clustered Bayesian Model Averaging . . . 883--908
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
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Bayesian Analysis
Volume 9, Number 1, March, 2014

         Francisco J. Rubio and   
               Mark F. J. Steel   Inference in Two-Piece Location-Scale
                                  Models with Jeffreys Priors  . . . . . . 1--22
        José M. Bernardo   Comment on Article by Rubio and Steel    23--24
                 James G. Scott   Comment on Article by Rubio and Steel    25--28
            Robert E. Weiss and   
                Marc A. Suchard   Comment on Article by Rubio and Steel    29--38
                       Xinyi Xu   Comment on Article by Rubio and Steel    39--44
         Francisco J. Rubio and   
               Mark F. J. Steel   Rejoinder  . . . . . . . . . . . . . . . 45--52
           Lorna M. Barclay and   
             Jane L. Hutton and   
                   Jim Q. Smith   Chain Event Graphs for Informed
                                  Missingness  . . . . . . . . . . . . . . 53--76
                 David A. Wooff   Bayes Linear Sufficiency in
                                  Non-exchangeable Multivariate Multiple
                                  Regressions  . . . . . . . . . . . . . . 77--96
        Theodore Papamarkou and   
            Antonietta Mira and   
                  Mark Girolami   Zero Variance Differential Geometric
                                  Markov Chain Monte Carlo Algorithms  . . 97--128
                 Erlis Ruli and   
             Nicola Sartori and   
                  Laura Ventura   Marginal Posterior Simulation via
                                  Higher-order Tail Area Approximations    129--146
      Luis E. Nieto-Barajas and   
Alberto Contreras-Cristán   A Bayesian Nonparametric Approach for
                                  Time Series Clustering . . . . . . . . . 147--170
            Friederike Greb and   
        Tatyana Krivobokova and   
                  Axel Munk and   
    Stephan von Cramon-Taubadel   Regularized Bayesian Estimation of
                                  Generalized Threshold Regression Models  171--196
            Cristiano Villa and   
              Stephen G. Walker   Objective Prior for the Number of
                                  Degrees of Freedom of a t Distribution   197--220
           Veronika Rockova and   
              Emmanuel Lesaffre   Incorporating Grouping Information in
                                  Bayesian Variable Selection with
                                  Applications in Genomics . . . . . . . . 221--258
                      Anonymous   Supplementary material . . . . . . . . . ??
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
                      Anonymous   Whole issue  . . . . . . . . . . . . . . ??

Bayesian Analysis
Volume 9, Number 2, June, 2014

               Zhihua Zhang and   
                 Dakan Wang and   
                  Guang Dai and   
              Michael I. Jordan   Matrix-Variate Dirichlet Process Priors
                                  with Applications  . . . . . . . . . . . 259--286
            Nammam A. Azadi and   
             Paul Fearnhead and   
              Gareth Ridall and   
                 Joleen H. Blok   Bayesian Sequential Experimental Design
                                  for Binary Response Data with
                                  Application to Electromyographic
                                  Experiments  . . . . . . . . . . . . . . 287--306
                  Juhee Lee and   
       Steven N. MacEachern and   
                  Yiling Lu and   
                Gordon B. Mills   Local-Mass Preserving Prior
                                  Distributions for Nonparametric Bayesian
                                  Models . . . . . . . . . . . . . . . . . 307--330
                 Ruitao Liu and   
         Arijit Chakrabarti and   
              Tapas Samanta and   
           Jayanta K. Ghosh and   
                    Malay Ghosh   On Divergence Measures Leading to
                                  Jeffreys and Other Reference Priors  . . 331--370
              Xin-Yuan Song and   
              Jing-Heng Cai and   
             Xiang-Nan Feng and   
                  Xue-Jun Jiang   Bayesian Analysis of the
                                  Functional-Coefficient Autoregressive
                                  Heteroscedastic Model  . . . . . . . . . 371--396
                Yu Ryan Yue and   
             Daniel Simpson and   
              Finn Lindgren and   
               Håvard Rue   Bayesian Adaptive Smoothing Splines
                                  Using Stochastic Differential Equations  397--424
      Jaakko Riihimäki and   
                    Aki Vehtari   Laplace Approximation for Logistic
                                  Gaussian Process Density Estimation and
                                  Regression . . . . . . . . . . . . . . . 425--448
                    Fei Liu and   
         Sounak Chakraborty and   
                     Fan Li and   
                    Yan Liu and   
              Aurelie C. Lozano   Bayesian Regularization via Graph
                                  Laplacian  . . . . . . . . . . . . . . . 449--474
               Catia Scricciolo   Adaptive Bayesian Density Estimation in
                                  $ L^p $-metrics with Pitman--Yor or
                                  Normalized Inverse-Gaussian Process
                                  Kernel Mixtures  . . . . . . . . . . . . 475--520
                      Anonymous   Supplementary material . . . . . . . . . ??
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
                      Anonymous   Whole issue  . . . . . . . . . . . . . . ??

Bayesian Analysis
Volume 9, Number 3, September, 2014

           Michael Finegold and   
                  Mathias Drton   Robust Bayesian Graphical Modeling Using
                                  Dirichlet $t$-Distributions  . . . . . . 521--550
      François Caron and   
                     Luke Bornn   Comment on Article by Finegold and Drton 551--556
                 Babak Shahbaba   Comment on Article by Finegold and Drton 557--560
                      Anonymous   Contributed Discussion on Article by
                                  Finegold and Drton . . . . . . . . . . . 561--590
           Michael Finegold and   
                  Mathias Drton   Rejoinder  . . . . . . . . . . . . . . . 591--596
          Timothy E. Hanson and   
           Adam J. Branscum and   
              Wesley O. Johnson   Informative $g$-Priors for Logistic
                                  Regression . . . . . . . . . . . . . . . 597--612
             George Casella and   
        Elías Moreno and   
         F. Javier Girón   Cluster Analysis, Model Selection, and
                                  Prior Distributions on Models  . . . . . 613--658
             A. Marie Fitch and   
           M. Beatrix Jones and   
         Hél\`ene Massam   The Performance of Covariance Selection
                                  Methods That Consider Decomposable
                                  Models Only  . . . . . . . . . . . . . . 659--684
           Joseph B. Kadane and   
           Steven N. MacEachern   Toward Rational Social Decisions: A
                                  Review and Some Results  . . . . . . . . 685--698
               Kuo-Jung Lee and   
             Galin L. Jones and   
             Brian S. Caffo and   
               Susan S. Bassett   Spatial Bayesian Variable Selection
                                  Models on Functional Magnetic Resonance
                                  Imaging Time-Series Data . . . . . . . . 699--732
                    Meng Li and   
               Subhashis Ghosal   Bayesian Multiscale Smoothing of
                                  Gaussian Noised Images . . . . . . . . . 733--758

Bayesian Analysis
Volume 9, Number 4, December, 2014

               Jesse Windle and   
             Carlos M. Carvalho   A Tractable State-Space Model for
                                  Symmetric Positive-Definite Matrices . . 759--792
                Roberto Casarin   Comment on Article by Windle and
                                  Carvalho . . . . . . . . . . . . . . . . 793--804
      Catherine Scipione Forbes   Comment on Article by Windle and
                                  Carvalho . . . . . . . . . . . . . . . . 805--808
          Enrique ter Horst and   
                  German Molina   Comment on Article by Windle and
                                  Carvalho . . . . . . . . . . . . . . . . 809--818
               Jesse Windle and   
             Carlos M. Carvalho   Rejoinder  . . . . . . . . . . . . . . . 819--822
Asael Fabian Martínez and   
          Ramsés H. Mena   On a Nonparametric Change Point
                                  Detection Model in Markovian Regimes . . 823--858
            Eduard Belitser and   
                    Paulo Serra   Adaptive Priors Based on Splines with
                                  Random Knots . . . . . . . . . . . . . . 859--882
               Henrik Nyman and   
               Johan Pensar and   
                 Timo Koski and   
                 Jukka Corander   Stratified Graphical Models ---
                                  Context-Specific Independence in
                                  Graphical Models . . . . . . . . . . . . 883--908
                David Shalloway   The Evidentiary Credible Region  . . . . 909--922
               Arkady Shemyakin   Hellinger Distance and Non-informative
                                  Priors . . . . . . . . . . . . . . . . . 923--938
             Isabelle Smith and   
           André Ferrari   Equivalence between the Posterior
                                  Distribution of the Likelihood Ratio and
                                  a $p$-value in an Invariant Frame  . . . 939--962
            Linda S. L. Tan and   
                  David J. Nott   A Stochastic Variational Framework for
                                  Fitting and Diagnosing Generalized
                                  Linear Mixed Models  . . . . . . . . . . 963--1004


Bayesian Analysis
Volume 10, Number 1, March, 2015

      Trevelyan J. McKinley and   
           Michelle Morters and   
               James L. N. Wood   Bayesian Model Choice in Cumulative Link
                                  Ordinal Regression Models  . . . . . . . 1--30
                Fumiyasu Komaki   Asymptotic Properties of Bayesian
                                  Predictive Densities When the
                                  Distributions of Data and Target
                                  Variables are Different  . . . . . . . . 31--51
                 Harold Bae and   
               Thomas Perls and   
           Martin Steinberg and   
               Paola Sebastiani   Bayesian Polynomial Regression Models to
                                  Fit Multiple Genetic Models for
                                  Quantitative Traits  . . . . . . . . . . 53--74
         Dimitris Fouskakis and   
          Ioannis Ntzoufras and   
                   David Draper   Power-Expected-Posterior Priors for
                                  Variable Selection in Gaussian Linear
                                  Models . . . . . . . . . . . . . . . . . 75--107
               A. Mohammadi and   
                      E. C. Wit   Bayesian Structure Learning in Sparse
                                  Gaussian Graphical Models  . . . . . . . 109--138
            Cyr Emile M'lan and   
                  Ming-Hui Chen   Objective Bayesian Inference for
                                  Bilateral Data . . . . . . . . . . . . . 139--170
        Fernando V. Bonassi and   
                      Mike West   Sequential Monte Carlo with Adaptive
                                  Weights for Approximate Bayesian
                                  Computation  . . . . . . . . . . . . . . 171--187

Bayesian Analysis
Volume 10, Number 2, June, 2015

               Zhihua Zhang and   
                         Jin Li   Compound Poisson Processes, Latent
                                  Shrinkage Priors and Bayesian Nonconvex
                                  Penalization . . . . . . . . . . . . . . 247--274
           Stanley I. M. Ko and   
        Terence T. L. Chong and   
                    Pulak Ghosh   Dirichlet Process Hidden Markov Multiple
                                  Change-point Model . . . . . . . . . . . 275--296
            Chris C. Holmes and   
      François Caron and   
             Jim E. Griffin and   
              David A. Stephens   Two-sample Bayesian Nonparametric
                                  Hypothesis Testing . . . . . . . . . . . 297--320
           Ma\lgorzata Roos and   
          Thiago G. Martins and   
              Leonhard Held and   
               Håvard Rue   Sensitivity Analysis for Bayesian
                                  Hierarchical Models  . . . . . . . . . . 321--349
                       Hao Wang   Scaling It Up: Stochastic Search
                                  Structure Learning in Graphical Models   351--377
            Garritt L. Page and   
           Fernando A. Quintana   Predictions Based on the Clustering of
                                  Heterogeneous Functions via Shape and
                                  Subject-Specific Covariates  . . . . . . 379--410
             Stefano Cabras and   
Maria Eugenia Castellanos Nueda and   
                     Erlis Ruli   Approximate Bayesian Computation by
                                  Modelling Summary Statistics in a
                                  Quasi-likelihood Framework . . . . . . . 411--439
                Lilia Costa and   
                  Jim Smith and   
             Thomas Nichols and   
              James Cussens and   
             Eugene P. Duff and   
                 Tamar R. Makin   Searching Multiregression Dynamic Models
                                  of Resting-State fMRI Networks Using
                                  Integer Programming  . . . . . . . . . . 441--478
            A. Philip Dawid and   
                   Monica Musio   Bayesian Model Selection Based on Proper
                                  Scoring Rules  . . . . . . . . . . . . . 479--499
          Matthias Katzfuss and   
           Anirban Bhattacharya   Comment on Article by Dawid and Musio    501--504
        Christopher M. Hans and   
                 Mario Peruggia   Comment on Article by Dawid and Musio    505--509
                 C. Grazian and   
                 I. Masiani and   
                   C. P. Robert   Comment on Article by Dawid and Musio    511--515
            A. Philip Dawid and   
                   Monica Musio   Rejoinder  . . . . . . . . . . . . . . . 517--521

Bayesian Analysis
Volume 10, Number 3, September, 2015

           Sergio Venturini and   
         Francesca Dominici and   
            Giovanni Parmigiani   Generalized Quantile Treatment Effect: A
                                  Flexible Bayesian Approach Using
                                  Quantile Ratio Smoothing . . . . . . . . 523--552
             Mauro Bernardi and   
          Ghislaine Gayraud and   
                   Lea Petrella   Bayesian Tail Risk Interdependence Using
                                  Quantile Regression  . . . . . . . . . . 553--603
                  Yajuan Si and   
           Natesh S. Pillai and   
                  Andrew Gelman   Bayesian Nonparametric Weighted Sampling
                                  Inference  . . . . . . . . . . . . . . . 605--625
          Douglas K. Sparks and   
              Kshitij Khare and   
                    Malay Ghosh   Necessary and Sufficient Conditions for
                                  High-Dimensional Posterior Consistency
                                  under $g$-Priors . . . . . . . . . . . . 627--664
                Maxim Panov and   
              Vladimir Spokoiny   Finite Sample Bernstein--von Mises
                                  Theorem for Semiparametric Problems  . . 665--710
  Gustavo da Silva Ferreira and   
                  Dani Gamerman   Optimal Design in Geostatistics under
                                  Preferential Sampling  . . . . . . . . . 711--735
            Michael Chipeta and   
                Peter J. Diggle   Comment on Article by Ferreira and
                                  Gamerman . . . . . . . . . . . . . . . . 737--739
               Noel Cressie and   
            Raymond L. Chambers   Comment on Article by Ferreira and
                                  Gamerman . . . . . . . . . . . . . . . . 741--748
                 James V. Zidek   Comment on Article by Ferreira and
                                  Gamerman . . . . . . . . . . . . . . . . 749--752
  Gustavo da Silva Ferreira and   
                  Dani Gamerman   Rejoinder  . . . . . . . . . . . . . . . 753--758

Bayesian Analysis
Volume 10, Number 4, December, 2015

          R. V. Ramamoorthi and   
             Karthik Sriram and   
                    Ryan Martin   On Posterior Concentration in
                                  Misspecified Models  . . . . . . . . . . 759--789
            Roberto Casarin and   
            Fabrizio Leisen and   
              German Molina and   
              Enrique ter Horst   A Bayesian Beta Markov Random Field
                                  Calibration of the Term Structure of
                                  Implied Risk Neutral Densities . . . . . 791--819
              Maria DeYoreo and   
              Athanasios Kottas   A Fully Nonparametric Modeling Approach
                                  to Binary Regression . . . . . . . . . . 821--847
             Rebecca C. Steorts   Entity Resolution with Empirically
                                  Motivated Priors . . . . . . . . . . . . 849--875
          Daniel Williamson and   
              Michael Goldstein   Posterior Belief Assessment: Extracting
                                  Meaningful Subjective Judgements from
                                  Bayesian Analyses with Complex
                                  Statistical Models . . . . . . . . . . . 877--908


Bayesian Analysis
Volume 11, Number 1, March, 2016

         Mohammad Arshad Rahman   Bayesian Quantile Regression for Ordinal
                                  Models . . . . . . . . . . . . . . . . . 1--24
                  O. Bodnar and   
                    A. Link and   
                      C. Elster   Objective Bayesian Inference for a
                                  Generalized Marginal Random Effects
                                  Model  . . . . . . . . . . . . . . . . . 25--45
           Daniel J. Graham and   
              Emma J. McCoy and   
              David A. Stephens   Approximate Bayesian Inference for
                                  Doubly Robust Estimation . . . . . . . . 47--69
         Adam Justin Suarez and   
               Subhashis Ghosal   Bayesian Clustering of Functional Data
                                  Using Local Features . . . . . . . . . . 71--98
                Riten Mitra and   
          Peter Müller and   
                        Yuan Ji   Bayesian Graphical Models for
                                  Differential Pathways  . . . . . . . . . 99--124
                Lutz Gruber and   
                      Mike West   GPU-Accelerated Bayesian Learning and
                                  Forecasting in Simultaneous Graphical
                                  Dynamic Linear Models  . . . . . . . . . 125--149
              Sophie Donnet and   
                Judith Rousseau   Bayesian Inference for Partially
                                  Observed Multiplicative Intensity
                                  Processes  . . . . . . . . . . . . . . . 151--190
            Brian P. Weaver and   
          Brian J. Williams and   
 Christine M. Anderson-Cook and   
                David M. Higdon   Computational Enhancements to Bayesian
                                  Design of Experiments Using Gaussian
                                  Processes  . . . . . . . . . . . . . . . 191--213
                 Nial Friel and   
            Antonietta Mira and   
                Chris. J. Oates   Exploiting Multi-Core Architectures for
                                  Reduced-Variance Estimation with
                                  Intractable Likelihoods  . . . . . . . . 215--245
                  Jie Xiong and   
Väinö Jääskinen and   
                 Jukka Corander   Recursive Learning for Sparse Markov
                                  Models . . . . . . . . . . . . . . . . . 247--263

Bayesian Analysis
Volume 11, Number 2, June, 2016

    Christopher C. Drovandi and   
         Anthony N. Pettitt and   
               Roy A. McCutchan   Exact and Approximate Bayesian Inference
                                  for Low Integer-Valued Time Series
                                  Models with Intractable Likelihoods  . . 325--352
              Hongmei Zhang and   
            Xianzheng Huang and   
                Jianjun Gan and   
           Wilfried Karmaus and   
              Tara Sabo-Attwood   A Two-Component $G$-Prior for Variable
                                  Selection  . . . . . . . . . . . . . . . 353--380
           Thomas A. Murray and   
             Brian P. Hobbs and   
          Daniel J. Sargent and   
              Bradley P. Carlin   Flexible Bayesian Survival Modeling with
                                  Semiparametric Time-Dependent and
                                  Shape-Restricted Covariate Effects . . . 381--402
               Joseph B. Kadane   Sums of Possibly Associated Bernoulli
                                  Variables: The Conway--Maxwell-Binomial
                                  Distribution . . . . . . . . . . . . . . 403--420
                  Hwan-sik Choi   Expert Information and Nonparametric
                                  Bayesian Inference of Rare Events  . . . 421--445
                  Wen Cheng and   
              Ian L. Dryden and   
                Xianzheng Huang   Bayesian Registration of Functions and
                                  Curves . . . . . . . . . . . . . . . . . 447--475
               Mengjie Chen and   
                   Chao Gao and   
                    Hongyu Zhao   Posterior Contraction Rates of the
                                  Phylogenetic Indian Buffet Processes . . 477--497
        Tracy A. Schifeling and   
               Jerome P. Reiter   Incorporating Marginal Prior Information
                                  in Latent Class Models . . . . . . . . . 499--518
Kelly C. M. Gonçalves and   
           Fernando A. S. Moura   A Mixture Model for Rare and Clustered
                                  Populations Under Adaptive Cluster
                                  Sampling . . . . . . . . . . . . . . . . 519--544
          Sarah E. Michalak and   
                 Carl N. Morris   Posterior Propriety for Hierarchical
                                  Models with Log-Likelihoods That Have
                                  Norm Bounds  . . . . . . . . . . . . . . 545--571
              Jeong Eun Lee and   
            Christian P. Robert   Importance Sampling Schemes for Evidence
                                  Approximation in Mixture Models  . . . . 573--597
                Zhuqing Liu and   
       Veronica J. Berrocal and   
         Andreas J. Bartsch and   
             Timothy D. Johnson   Pre-surgical fMRI Data Analysis Using a
                                  Spatially Adaptive Conditionally
                                  Autoregressive Model . . . . . . . . . . 599--625

Bayesian Analysis
Volume 11, Number 3, September, 2016

                  Peter D. Hoff   Equivariant and Scale-Free Tucker
                                  Decomposition Models . . . . . . . . . . 627--648
              Jingjing Yang and   
               Hongxiao Zhu and   
               Taeryon Choi and   
                  Dennis D. Cox   Smoothing and Mean-Covariance Estimation
                                  of Functional Data with a Bayesian
                                  Hierarchical Model . . . . . . . . . . . 649--670
          Alen Alexanderian and   
            Philip J. Gloor and   
                   Omar Ghattas   On Bayesian $A$- and $D$-Optimal
                                  Experimental Designs in Infinite
                                  Dimensions . . . . . . . . . . . . . . . 671--695
                  S. Favaro and   
                   A. Lijoi and   
                    C. Nava and   
                  B. Nipoti and   
           I. Prünster and   
                      Y. W. Teh   On the Stick-Breaking Representation for
                                  Homogeneous NRMIs  . . . . . . . . . . . 697--724
            A. Philip Dawid and   
               Monica Musio and   
            Stephen E. Fienberg   From Statistical Evidence to Evidence of
                                  Causality  . . . . . . . . . . . . . . . 725--752
            Prasenjit Ghosh and   
               Xueying Tang and   
                Malay Ghosh and   
             Arijit Chakrabarti   Asymptotic Properties of Bayes Risk of a
                                  General Class of Shrinkage Priors in
                                  Multiple Hypothesis Testing Under
                                  Sparsity . . . . . . . . . . . . . . . . 753--796
                  Ruibin Xi and   
                 Yunxiao Li and   
                      Yiming Hu   Bayesian Quantile Regression Based on
                                  the Empirical Likelihood with Spike and
                                  Slab Priors  . . . . . . . . . . . . . . 821--855
   Caitríona M. Ryan and   
    Christopher C. Drovandi and   
             Anthony N. Pettitt   Optimal Bayesian Experimental Design for
                                  Models with Intractable Likelihoods
                                  Using Indirect Inference Applied to
                                  Biological Process Models  . . . . . . . 857--883
             Matthew T. Pratola   Efficient Metropolis--Hastings Proposal
                                  Mechanisms for Bayesian Regression Tree
                                  Models . . . . . . . . . . . . . . . . . 885--911
              Robert B. Gramacy   Comment on Article by Pratola  . . . . . 913--919
            Christopher M. Hans   Comment on Article by Pratola  . . . . . 921--927
        Oksana A. Chkrebtii and   
             Scotland Leman and   
               Andrew Hoegh and   
          Reihaneh Entezari and   
              Radu V. Craiu and   
       Jeffrey S. Rosenthal and   
        Abdolreza Mohammadi and   
            Maurits Kaptein and   
               Luca Martino and   
            Rafael B. Stern and   
              Francisco Louzada   Contributed Discussion on Article by
                                  Pratola  . . . . . . . . . . . . . . . . 929--943
             Matthew T. Pratola   Rejoinder  . . . . . . . . . . . . . . . 945--955
                      Anonymous   Editorial Board  . . . . . . . . . . . . ??
                      Anonymous   Table of Contents  . . . . . . . . . . . ??
           Tony Pourmohamad and   
              Herbert K. H. Lee   Multivariate Stochastic Process Models
                                  for Correlated Responses of Mixed Type   797--820

Bayesian Analysis
Volume 11, Number 4, December, 2016

              Chin-I. Cheng and   
               Paul L. Speckman   Bayes Factors for Smoothing Spline ANOVA 957--975
               Wen-Hsi Yang and   
             Scott H. Holan and   
           Christopher K. Wikle   Bayesian Lattice Filters for
                                  Time-Varying Autoregression and
                                  Time-Frequency Analysis  . . . . . . . . 977--1003
            N. T. Underhill and   
                    J. Q. Smith   Context-Dependent Score Based Bayesian
                                  Information Criteria . . . . . . . . . . 1005--1033
           Samantha Leorato and   
                 Maura Mezzetti   Spatial Panel Data Model with Error
                                  Dependence: A Bayesian Separable
                                  Covariance Approach  . . . . . . . . . . 1035--1069
                Nadja Klein and   
                   Thomas Kneib   Scale-Dependent Priors for Variance
                                  Parameters in Structured Additive
                                  Distributional Regression  . . . . . . . 1071--1106
J. Pablo Arias-Nicolás and   
           Fabrizio Ruggeri and   
  Alfonso Suárez-Llorens   New Classes of Priors Based on
                                  Stochastic Orders and Distortion
                                  Functions  . . . . . . . . . . . . . . . 1107--1136
            Seonghyun Jeong and   
                  Taeyoung Park   Bayesian Semiparametric Inference on
                                  Functional Relationships in Linear Mixed
                                  Models . . . . . . . . . . . . . . . . . 1137--1163
         Rodrigo A. Collazo and   
                   Jim Q. Smith   A New Family of Non-Local Priors for
                                  Chain Event Graph Model Selection  . . . 1165--1201
              Tingting Zhao and   
                  Ziyu Wang and   
      Alexander Cumberworth and   
              Joerg Gsponer and   
           Nando de Freitas and   
Alexandre Bouchard-Côté   Bayesian Analysis of Continuous Time
                                  Markov Chains with Application to
                                  Phylogenetic Modelling . . . . . . . . . 1203--1237
        Oksana A. Chkrebtii and   
          David A. Campbell and   
             Ben Calderhead and   
               Mark A. Girolami   Bayesian Solution Uncertainty
                                  Quantification for Differential
                                  Equations  . . . . . . . . . . . . . . . 1239--1267
                    Martin Lysy   Comment on Article by Chkrebtii,
                                  Campbell, Calderhead, and Girolami . . . 1269--1273
                  Sarat C. Dass   Comment on Article by Chkrebtii,
                                  Campbell, Calderhead, and Girolami . . . 1275--1277
            Bani K. Mallick and   
                 Keren Yang and   
               Nilabja Guha and   
               Yalchin Efendiev   Comment on Article by Chkrebtii,
                                  Campbell, Calderhead, and Girolami . . . 1279--1284
François-Xavier Briol and   
               Jon Cockayne and   
                Onur Teymur and   
         William Weimin Yoo and   
               Jon Cockayne and   
            Michael Schober and   
                 Philipp Hennig   Contributed Discussion on Article by
                                  Chkrebtii, Campbell, Calderhead, and
                                  Girolami . . . . . . . . . . . . . . . . 1285--1293
        Oksana A. Chkrebtii and   
          David A. Campbell and   
             Ben Calderhead and   
               Mark A. Girolami   Rejoinder  . . . . . . . . . . . . . . . 1295--1299
                      Anonymous   Editorial Board  . . . . . . . . . . . . ??
                      Anonymous   Table of Contents  . . . . . . . . . . . ??


Bayesian Analysis
Volume 12, Number 1, March, 2017

        Thomas J. Leininger and   
                Alan E. Gelfand   Bayesian Inference and Model Assessment
                                  for Spatial Point Patterns Using
                                  Posterior Predictive Samples . . . . . . 1--30
                 Haolun Shi and   
                   Guosheng Yin   Bayesian Two-Stage Design for Phase II
                                  Clinical Trials with Switching
                                  Hypothesis Tests . . . . . . . . . . . . 31--51
              Sophie Donnet and   
          Vincent Rivoirard and   
            Judith Rousseau and   
               Catia Scricciolo   Posterior Concentration Rates for
                                  Counting Processes with Aalen
                                  Multiplicative Intensities . . . . . . . 53--87
                   Bo Jiang and   
                    Chao Ye and   
                     Jun S. Liu   Bayesian Nonparametric Tests via Sliced
                                  Inverse Modeling . . . . . . . . . . . . 89--112
Daniel Hernandez-Stumpfhauser and   
              F. Jay Breidt and   
          Mark J. van der Woerd   The General Projected Normal
                                  Distribution of Arbitrary Dimension:
                                  Modeling and Bayesian Inference  . . . . 113--133
                Jim Griffin and   
                     Phil Brown   Hierarchical Shrinkage Priors for
                                  Regression Models  . . . . . . . . . . . 135--159
                Genya Kobayashi   Bayesian Endogenous Tobit Quantile
                                  Regression . . . . . . . . . . . . . . . 161--191
          Lawrence Bardwell and   
                 Paul Fearnhead   Bayesian Detection of Abnormal Segments
                                  in Multiple Time Series  . . . . . . . . 193--218
                Paulo Serra and   
            Tatyana Krivobokova   Adaptive Empirical Bayesian Smoothing
                                  Splines  . . . . . . . . . . . . . . . . 219--238
 Miguel A. Martinez-Beneito and   
    Paloma Botella-Rocamora and   
               Sudipto Banerjee   Towards a Multidimensional Approach to
                                  Bayesian Disease Mapping . . . . . . . . 239--259

Bayesian Analysis
Volume 12, Number 2, June, 2017

             Adam J. Suarez and   
               Subhashis Ghosal   Bayesian Estimation of Principal
                                  Components for Functional Data . . . . . 311--333
                    Bin Zhu and   
                David B. Dunson   Bayesian Functional Data Modeling for
                                  Heterogeneous Volatility . . . . . . . . 335--350
           Daniel K. Sewell and   
                     Yuguo Chen   Latent Space Approaches to Community
                                  Detection in Dynamic Networks  . . . . . 351--377
                 Seongil Jo and   
                Jaeyong Lee and   
          Peter Müller and   
       Fernando A. Quintana and   
                 Lorenzo Trippa   Dependent Species Sampling Models for
                                  Spatial Density Estimation . . . . . . . 379--406
           Fabrizio Ruggeri and   
                Zaid Sawlan and   
              Marco Scavino and   
                   Raul Tempone   A Hierarchical Bayesian Setting for an
                                  Inverse Problem in Linear Parabolic PDEs
                                  with Noisy Boundary Conditions . . . . . 407--433
          Gavin A. Whitaker and   
           Andrew Golightly and   
            Richard J. Boys and   
                 Chris Sherlock   Bayesian Inference for Diffusion-Driven
                                  Mixed-Effects Models . . . . . . . . . . 435--463
               Daniel Turek and   
           Perry de Valpine and   
    Christopher J. Paciorek and   
      Clifford Anderson-Bergman   Automated Parameter Blocking for
                                  Efficient Markov Chain Monte Carlo
                                  Sampling . . . . . . . . . . . . . . . . 465--490
           Osvaldo Anacleto and   
                 Catriona Queen   Dynamic Chain Graph Models for Time
                                  Series Network Data  . . . . . . . . . . 491--509
                       Min Wang   Mixtures of $g$-Priors for Analysis of
                                  Variance Models with a Diverging Number
                                  of Parameters  . . . . . . . . . . . . . 511--532
               Hyungsuk Tak and   
                 Carl N. Morris   Data-Dependent Posterior Propriety of a
                                  Bayesian Beta-Binomial-Logit Model . . . 533--555
              Cecilia Earls and   
                   Giles Hooker   Variational Bayes for Functional Data
                                  Registration, Smoothing, and Prediction  557--582
               Sudipto Banerjee   High-Dimensional Bayesian Geostatistics  583--614

Bayesian Analysis
Volume 12, Number 3, September, 2017

María-Eglée Pérez and   
  Luis Raúl Pericchi and   
 Isabel Cristina Ramírez   The Scaled Beta2 Distribution as a
                                  Robust Prior for Scales  . . . . . . . . 615--637
                  Yanxun Xu and   
             Peter F. Thall and   
          Peter Müller and   
                 Mehran J. Reza   A Decision-Theoretic Comparison of
                                  Treatments to Resolve Air Leaks After
                                  Lung Surgery Based on Nonparametric
                                  Modeling . . . . . . . . . . . . . . . . 639--652
            Jeffrey D. Hart and   
                   Taeryon Choi   Nonparametric Goodness of Fit via
                                  Cross-Validation Bayes Factors . . . . . 653--677
              Maria DeYoreo and   
           Jerome P. Reiter and   
           D. Sunshine Hillygus   Bayesian Mixture Models with Focused
                                  Clustering for Mixed Ordinal and Nominal
                                  Data . . . . . . . . . . . . . . . . . . 679--703
             Luai Al Labadi and   
                  Michael Evans   Optimal Robustness Results for Relative
                                  Belief Inferences and the Relationship
                                  to Prior-Data Conflict . . . . . . . . . 705--728
               Silvia Polettini   A Generalised Semiparametric Bayesian
                                  Fay--Herriot Model for Small Area
                                  Estimation Shrinking Both Means and
                                  Variances  . . . . . . . . . . . . . . . 729--752
            Vivekananda Roy and   
             Sounak Chakraborty   Selection of Tuning Parameters, Solution
                                  Paths and Standard Errors for Bayesian
                                  Lassos . . . . . . . . . . . . . . . . . 753--778
                          Li Ma   Adaptive Shrinkage in Pólya Tree Type
                                  Models . . . . . . . . . . . . . . . . . 779--805
                     Tri Le and   
                Bertrand Clarke   A Bayes Interpretation of Stacking for
                                  $M$-Complete and $M$-Open Settings . . . 807--829
                 Zach Shahn and   
                  David Madigan   Latent Class Mixture Models of Treatment
                                  Effect Heterogeneity . . . . . . . . . . 831--854
Daniel Taylor-Rodríguez and   
           Andrew J. Womack and   
            Claudio Fuentes and   
               Nikolay Bliznyuk   Intrinsic Bayesian Analysis for
                                  Occupancy Models . . . . . . . . . . . . 855--877

Bayesian Analysis
Volume 12, Number 4, December, 2017

              Sarah Filippi and   
                Chris C. Holmes   A Bayesian Nonparametric Approach to
                                  Testing for Dependence Between Random
                                  Variables  . . . . . . . . . . . . . . . 919--938
Daniel Taylor-Rodríguez and   
           Kimberly Kaufeld and   
            Erin M. Schliep and   
             James S. Clark and   
                Alan E. Gelfand   Joint Species Distribution Modeling:
                                  Dimension Reduction Using Dirichlet
                                  Processes  . . . . . . . . . . . . . . . 939--967
                David Puelz and   
            P. Richard Hahn and   
             Carlos M. Carvalho   Variable Selection in Seemingly
                                  Unrelated Regressions with Random
                                  Predictors . . . . . . . . . . . . . . . 969--989
              Clara Grazian and   
                  Brunero Liseo   Approximate Bayesian Inference in
                                  Semiparametric Copula Models . . . . . . 991--1016
                 Yulai Cong and   
                    Bo Chen and   
                  Mingyuan Zhou   Fast Simulation of Hyperplane-Truncated
                                  Multivariate Normal Distributions  . . . 1017--1037
                  B. Liquet and   
               K. Mengersen and   
              A. N. Pettitt and   
                      M. Sutton   Bayesian Variable Selection Regression
                                  of Multivariate Responses for Group Data 1039--1067
        Peter Grünwald and   
                Thijs van Ommen   Inconsistency of Bayesian Inference for
                                  Misspecified Linear Models, and a
                                  Proposal for Repairing It  . . . . . . . 1069--1103
             Anindya Bhadra and   
            Jyotishka Datta and   
         Nicholas G. Polson and   
                Brandon Willard   The Horseshoe+ Estimator of Ultra-Sparse
                                  Signals  . . . . . . . . . . . . . . . . 1105--1131
            Prasenjit Ghosh and   
             Arijit Chakrabarti   Asymptotic Optimality of One-Group
                                  Shrinkage Priors in Sparse
                                  High-dimensional Problems  . . . . . . . 1133--1161
     P. Ramírez-Cobo and   
                R. E. Lillo and   
                    M. P. Wiper   Bayesian Analysis of the Stationary
                                  MAP$_2$  . . . . . . . . . . . . . . . . 1163--1194
               Johan Pensar and   
               Henrik Nyman and   
              Juha Niiranen and   
                 Jukka Corander   Marginal Pseudo-Likelihood Learning of
                                  Discrete Markov Network Structures . . . 1195--1215
             Karthik Sriram and   
              R. V. Ramamoorthi   Correction to: ``Posterior Consistency
                                  of Bayesian Quantile Regression Based on
                                  the Misspecified Asymmetric Laplace
                                  Density''  . . . . . . . . . . . . . . . 1217--1219
Stéphanie van der Pas and   
        Botond Szabó and   
              Aad van der Vaart   Uncertainty Quantification for the
                                  Horseshoe (with Discussion)  . . . . . . 1221--1274
         Nicholas G. Polson and   
                  Vadim Sokolov   Deep Learning: A Bayesian Perspective    1275--1304


Bayesian Analysis
Volume 13, Number 1, March, 2018

            Maria A. Terres and   
         Montserrat Fuentes and   
            Dean Hesterberg and   
             Matthew Polizzotto   Bayesian Spectral Modeling for
                                  Multivariate Spatial Distributions of
                                  Elemental Concentrations in Soil . . . . 1--28
            Daniele Durante and   
                David B. Dunson   Bayesian Inference and Testing of Group
                                  Differences in Brain Networks  . . . . . 29--58
              Sindhu Ghanta and   
             Jennifer G. Dy and   
                Donglin Niu and   
              Michael I. Jordan   Latent Marked Poisson Process with
                                  Applications to Object Segmentation  . . 85--113
       Ruby Chiu-Hsing Weng and   
                D. Stephen Coad   Real-Time Bayesian Parameter Estimation
                                  for Item Response Models . . . . . . . . 115--137
    Christopher C. Drovandi and   
                 Minh-Ngoc Tran   Improving the Efficiency of Fully
                                  Bayesian Optimal Design of Experiments
                                  Using Randomised Quasi-Monte Carlo . . . 139--162
            P. Richard Hahn and   
         Carlos M. Carvalho and   
                David Puelz and   
                      Jingyu He   Regularization and Confounding in Linear
                                  Regression for Treatment Effect
                                  Estimation . . . . . . . . . . . . . . . 163--182
                Jingchen Hu and   
           Jerome P. Reiter and   
                    Quanli Wang   Dirichlet Process Mixture Models for
                                  Modeling and Generating Synthetic
                                  Versions of Nested Categorical Data  . . 183--200
             James Johndrow and   
           Anirban Bhattacharya   Optimal Gaussian Approximations to the
                                  Posterior for Log-Linear Models with
                                  Diaconis--Ylvisaker Priors . . . . . . . 201--223
          James R. Faulkner and   
              Vladimir N. Minin   Locally Adaptive Smoothing with Markov
                                  Random Fields and Shrinkage Priors . . . 225--252

Bayesian Analysis
Volume 13, Number 2, June, 2018

                 Yu-Bo Wang and   
              Ming-Hui Chen and   
                   Lynn Kuo and   
                  Paul O. Lewis   A New Monte Carlo Method for Estimating
                                  Marginal Likelihoods . . . . . . . . . . 311--333
        Daniel A. Henderson and   
                Liam J. Kirrane   A Comparison of Truncated and
                                  Time-Weighted Plackett--Luce Models for
                                  Probabilistic Forecasting of Formula One
                                  Results  . . . . . . . . . . . . . . . . 335--358
                Joyee Ghosh and   
                  Yingbo Li and   
                    Robin Mitra   On the Use of Cauchy Prior Distributions
                                  for Bayesian Logistic Regression . . . . 359--383
             Tevfik Aktekin and   
                Nick Polson and   
                    Refik Soyer   Sequential Bayesian Analysis of
                                  Multivariate Count Data  . . . . . . . . 385--409
                  Lili Zhao and   
                Weisheng Wu and   
                   Dai Feng and   
                  Hui Jiang and   
                XuanLong Nguyen   Bayesian Analysis of RNA-Seq Data Using
                                  a Family of Negative Binomial Models . . 411--436
        Panayiota Touloupou and   
             Naif Alzahrani and   
                 Peter Neal and   
        Simon E. F. Spencer and   
          Trevelyan J. McKinley   Efficient Model Comparison Techniques
                                  for Models Requiring Large Scale Data
                                  Augmentation . . . . . . . . . . . . . . 437--459
          Jean-Bernard Salomond   Testing Un-Separated Hypotheses by
                                  Estimating a Distance  . . . . . . . . . 461--484
                Cheng Zhang and   
             Babak Shahbaba and   
                   Hongkai Zhao   Variational Hamiltonian Monte Carlo via
                                  Score Matching . . . . . . . . . . . . . 485--506
         Christopher Nemeth and   
                 Chris Sherlock   Merging MCMC Subposteriors through
                                  Gaussian-Process Approximations  . . . . 507--530
            Hamid Zareifard and   
       Majid Jafari Khaledi and   
             Firoozeh Rivaz and   
         Mohammad Q. Vahidi-Asl   Modeling Skewed Spatial Data Using a
                                  Convolution of Gaussian and Log-Gaussian
                                  Processes  . . . . . . . . . . . . . . . 531--557
                  Sara Wade and   
              Zoubin Ghahramani   Bayesian Cluster Analysis: Point
                                  Estimation and Credible Balls (with
                                  Discussion)  . . . . . . . . . . . . . . 559--626
             Guido Consonni and   
         Dimitris Fouskakis and   
              Brunero Liseo and   
              Ioannis Ntzoufras   Prior Distributions for Objective
                                  Bayesian Analysis  . . . . . . . . . . . 627--679

Bayesian Analysis
Volume 13, Number 3, September, 2018

           Laura Forastiere and   
            Fabrizia Mealli and   
                  Luke Miratrix   Posterior Predictive $p$-Values with
                                  Fisher Randomization Tests in
                                  Noncompliance Settings: Test Statistics
                                  vs Discrepancy Measures  . . . . . . . . 681--701
            Zacharie Naulet and   
              Éric Barat   Some Aspects of Symmetric Gamma Process
                                  Mixtures . . . . . . . . . . . . . . . . 703--720
         Dimitris Fouskakis and   
          Ioannis Ntzoufras and   
          Konstantinos Perrakis   Power-Expected-Posterior Priors for
                                  Generalized Linear Models  . . . . . . . 721--748
             Kevin James Wilson   Specification of Informative Prior
                                  Distributions for Multinomial Models
                                  Using Vine Copulas . . . . . . . . . . . 749--766
          S. L. van der Pas and   
            A. W. van der Vaart   Bayesian Community Detection . . . . . . 767--796
  Alexander Y. Shestopaloff and   
                Radford M. Neal   Sampling Latent States for
                                  High-Dimensional Non-Linear State Space
                                  Models with the Embedded HMM Method  . . 797--822
                  Yan Zhang and   
              Howard D. Bondell   Variable Selection via Penalized
                                  Credible Regions with Dirichlet--Laplace
                                  Global-Local Shrinkage Priors  . . . . . 823--844
           Sonia Migliorati and   
     Agnese Maria Di Brisco and   
                  Andrea Ongaro   A New Regression Model for Bounded
                                  Responses  . . . . . . . . . . . . . . . 845--872
              Edward Higson and   
               Will Handley and   
                Mike Hobson and   
                Anthony Lasenby   Sampling Errors in Nested Sampling
                                  Parameter Estimation . . . . . . . . . . 873--896
                Jim Griffin and   
                Fabrizio Leisen   Modelling and Computation Using NCoRM
                                  Mixtures for Density Regression  . . . . 897--916
                 Yuling Yao and   
                Aki Vehtari and   
             Daniel Simpson and   
                  Andrew Gelman   Using Stacking to Average Bayesian
                                  Predictive Distributions (with
                                  Discussion)  . . . . . . . . . . . . . . 917--1003
           Joseph B. Kadane and   
              Galit Shmueli and   
            Thomas P. Minka and   
               Sharad Borle and   
               Peter Boatwright   Note of correction: ``Conjugate Analysis
                                  of the Conway--Maxwell--Poisson
                                  Distribution'' . . . . . . . . . . . . . 1005

Bayesian Analysis
Volume 13, Number 4, December, 2018

                      Hang Qian   Big Data Bayesian Linear Regression and
                                  Variable Selection by
                                  Normal-Inverse-Gamma Summation . . . . . 1007--1031
   Yuttapong Thawornwattana and   
             Daniel Dalquen and   
                    Ziheng Yang   Designing Simple and Efficient Markov
                                  Chain Monte Carlo Proposal Kernels . . . 1033--1059
                  Mingyuan Zhou   Nonparametric Bayesian Negative Binomial
                                  Factor Analysis  . . . . . . . . . . . . 1061--1089
                    Yang Ni and   
                    Yuan Ji and   
              Peter Müller   Reciprocal Graphical Models for
                                  Integrative Gene Regulatory Network
                                  Analysis . . . . . . . . . . . . . . . . 1091--1106
             Lutz F. Gruber and   
                  Claudia Czado   Bayesian Model Selection of Regular Vine
                                  Copulas  . . . . . . . . . . . . . . . . 1107--1131
                  Biao Yang and   
         Jonathan R. Stroud and   
                 Gabriel Huerta   Sequential Monte Carlo Smoothing with
                                  Parameter Estimation . . . . . . . . . . 1133--1157
                 Chong Wang and   
                  David M. Blei   A General Method for Robust Bayesian
                                  Modeling . . . . . . . . . . . . . . . . 1159--1187
               Joris Mulder and   
      Luis Raúl Pericchi   The Matrix-$F$ Prior for Estimating and
                                  Testing Covariance Matrices  . . . . . . 1189--1210
              Kyoungjae Lee and   
                    Jaeyong Lee   Optimal Bayesian Minimax Rates for
                                  Unconstrained Large Covariance Matrices  1211--1229
       Federico Castelletti and   
             Guido Consonni and   
      Marco L. Della Vedova and   
                 Stefano Peluso   Learning Markov Equivalence Classes of
                                  Directed Acyclic Graphs: An Objective
                                  Bayes Approach . . . . . . . . . . . . . 1231--1256