International Society for Bayesian Analysis

The December 2011 issue of the electronic journal BAYESIAN ANALYSIS has been published at http://ba.stat.cmu.edu.

This issue of BA features a paper on multiple changepoint models by Jason Wyse, Nial Friel, and Havard Rue.  The integrated nested Laplace approximation is employed for computational efficiency.  Additional perspective appears in discussions by Paul Fearnhead and Gary Koop.  This issue also contains many other fine articles across the field of Bayesian statistics.
 
We hope you will enjoy the issue, and as always we welcome your submissions at
 
http://ba.stat.cmu.edu/submit/
 
The December 2011 issue includes the following articles:
 
2011, Volume 06, Number 04, pp. 501--926
 
* Approximate simulation-free Bayesian inference for multiple changepoint models with dependence within segments, by Jason Wyse, Nial Friel and Havard Rue, pp. 501 - 528, posted online 2011-10-31, DOI:10.1214/11-BA620
 
       + Comment on Article by Wyse et al., by Paul Fearnhead, pp. 529 - 532, posted online 2011-11-14, DOI:10.1214/11-BA620A
 
       + Comment on Article by Wyse et al., by Gary Koop, pp. 533 - 540, posted online 2011-11-14, DOI:10.1214/11-BA620B
 
       + Rejoinder, by Jason Wyse, Nial Friel and Havard Rue, pp. 541 - 546, posted online 2011-11-14, DOI:10.1214/11-BA620REJ
 
* Impact of Beliefs About Atlantic Tropical Cyclone Detection on Conclusions About Trends in Tropical Cyclone Numbers, by Surya T. Tokdar, Iris Grossmann, Joseph B. Kadane, Anne-Sophie Charest, and Mitchell J. Small, pp. 547 - 572, posted online 2011-08-29, DOI:10.1214/11-BA621
 
* Model based clustering for three-way data structures, by Cinzia Viroli, pp. 573 - 602, posted online 2011-08-29, DOI:10.1214/11-BA622
 
 * Neutral-data comparisons for Bayesian testing, by Dan J. Spitzner, pp. 603 - 638, posted online 2011-08-29, DOI:10.1214/11-BA623
 
 * Dynamic Financial Index Models: Modeling Conditional Dependencies via Graphs, by Hao Wang, Craig Reeson and Carlos M. Carvalho, pp. 639 - 664, posted online 2011-09-13, DOI:10.1214/11-BA624
 
 * Bayesian Outlier Detection with Dirichlet Process Mixtures, by Matthew S. Shotwell and Elizabeth H. Slatey, pp. 665 - 690, posted online 2011-09-16, DOI:10.1214/11-BA625
 
 * Product partition models with correlated parameters, by Joao V. D. Monteiro, Renato M. Assuncao and Rosangela H. Loschi, pp. 691 - 726, posted online 2011-09-16, DOI:10.1214/11-BA626
 
 * Estimating a bivariate linear relationship, by David Leonard, pp. 727 - 754, posted online 2011-09-21, DOI:10.1214/11-BA627
 
 * Bayesian Cointegrated Vector Autoregression Models Incorporating alpha-stable Noise for Inter-day Price Movements Via Approximate Bayesian Computation, by Gareth W. Peters, Balakrishnan Kannan, Ben Lasscock, Chris Mellen and Simon Godsill, pp. 755 - 792, posted online , DOI:10.1214/11-BA628
 
 * A Computational Bayesian Method for Estimating the Number of Knots In Regression Splines, by Minjung Kyung, pp. 793 - 828, posted online 2011-09-28, DOI:10.1214/11-BA629
 
 * Bayesian clustering in decomposable graphs, by Luke Bornn and Francois Caron, pp. 829 - 846, posted online 2011-09-23, DOI:10.1214/11-BA630
 
 * Mean Field Variational Bayes for Elaborate Distributions, by Matthew P. Wand, John T. Ormerod, Simone A. Padoan and Rudolf Fruhrwirth, pp. 847 - 900, posted online 2011-09-27, DOI:10.1214/11-BA631
 
 * Bayesian Nonparametric Modelling of the Return Distribution with Stochastic Volatility, by Eleni-Ioanna Delatola and Jim E. Griffin, pp. 901 - 926, posted online 2011-09-28, DOI:10.1214/11-BA632
 
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 The journal is sponsored by the International Society for Bayesian Analysis (ISBA). Its editors are Ming-Hui Chen, Kate Cowles, David Dunson, David Heckerman, Valen Johnson, Antonietta Mira, Sonia Petrone, Bruno Sanso, Mark Steel, and Kert Viele. Herbie Lee is serving as Editor-in-Chief, Alyson Wilson is Managing Editor, Kary Myers is Production Editor, and Pantelis Vlachos is System Managing Editor.
 
 Bayesian Analysis seeks to publish a wide range of articles that demonstrate or discuss Bayesian methods in some theoretical or applied context. The journal welcomes submissions involving presentation of new computational and statistical methods; reviews, criticism, and discussion of existing approaches; historical perspectives; description of important scientific or policy application areas; case studies; and methods for experimental design, data collection, data sharing, or data mining. Evaluation of submissions is based on importance of content and effectiveness of communication.