--
Heidi Sestrich
Department of Statistics
Carnegie Mellon University
412-268-2718


A new issue of the new electronic journal BAYESIAN ANALYSIS has been
published at http://ba.stat.cmu.edu.

This issue of BA features a paper on spatial quantile regression by
Kristian Lum and Alan Gelfand, which provides a new model for spatial
data with covariates.  Additional perspective appears in discussions
by Rajarshi Guhaniyogi and Sudipto Banerjee, by Nan Lin and Chao
Chang, and by Marco Ferreira.  This issue also contains other fine
articles in nonparametric and parametric modeling.


We hope you will enjoy the issue,
and as always we welcome your submissions at
http://ba.stat.cmu.edu/submit/


The June 2012 issue includes the following articles:

2012, Volume 07, Number 02, pp. 235--502

* Spatial Quantile Multiple Regression Using the Asymmetric Laplace
  Process, by Kristian Lum and Alan Gelfand, pp. 235 - 258, posted
  online 2012-01-12, DOI:10.1214/12-BA708

        - Comment on Article by Lum and Gelfand, by Rajarshi
              Guhaniyogi and Sudipto Banerjee, pp. 259 - 262, posted
              online 2012-05-22, DOI:10.1214/12-BA708A
    
        - Comment on Article by Lum and Gelfand, by Nan Lin and Chao
              Chang, pp. 263 - 270, posted online 2012-05-22,
              DOI:10.1214/12-BA708B

        - Comment on Article by Lum and Gelfand, by Marco
              A. R. Ferreira, pp. 271 - 272, posted online 2012-05-22,
              DOI:10.1214/12-BA708C

        - Rejoinder, by Kristian Lum and Alan Gelfand, pp. 273 - 276,
              posted online 2012-05-22, DOI:10.1214/12-BA708REJ


* On the Support of MacEachern's Dependent Dirichlet Processes and
  Extensions, by Andres F. Barrientos, Alejandro Jara and Fernando
  A. Quintana, pp. 277 - 310, posted online 2012-01-03,
  DOI:10.1214/12-BA709

* Posterior Concentration Rates for Infinite Dimensional Exponential
  Families, by Vincent Rivoirard and Judith Rousseau, pp. 311 - 334,
  posted online 2012-01-05, DOI:10.1214/12-BA710

* Mixture Modeling for Marked Poisson Processes, by Matthew A. Taddy
  and Athanasios Kottas, pp. 335 - 362, posted online 2012-01-24,
  DOI:10.1214/12-BA711

* Objective Bayesian Analysis of a Measurement Error Small Area Model,
  by Serena Arima, Gauri S. Datta and Brunero Liseo, pp. 363 - 384,
  posted online 2012-02-20, DOI:10.1214/12-BA712

* Bayesian Model Selection for Beta Autoregressive Processes, by
  Roberto Casarin, Luciana Dalla Valle and Fabrizio Leisen, pp. 385 -
  410, posted online 2012-02-20, DOI:10.1214/12-BA713

* Log-Linear Pool to Combine Prior Distributions: A Suggestion for a
  Calibration-Based Approach, by M. J. Rufo, J. Martin and
  C. J. Perez, pp. 411 - 438, posted online 2012-01-13,
  DOI:10.1214/12-BA714

* Beta Processes, Stick-Breaking, and Power Laws, by Tamara Broderick,
  Michael I. Jordan and Jim Pitman, pp. 439 - 476, posted online
  2012-01-03, DOI:10.1214/12-BA715

* Regularization in Regression: Comparing Bayesian and Frequentist
  Methods in a Poorly Informative Situation, by Gilles Celeux,
  Mohammed El Anbari, Jean-Michel Marin and Christian P. Robert,
  pp. 477 - 502, posted online 2012-01-19, DOI:10.1214/12-BA716

    


                       *****

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
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.


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