A new issue of the new electronic
journal BAYESIAN ANALYSIS has been
published at http://ba.stat.cmu.edu.
In this "back to school" issue of
Bayesian Analysis, our discussion paper
concerns
two subjects of longstanding interest to
Bayesian modelers: variable selection,
and the linking of two kinds of
high-dimensional data. In their
interesting article,
Stefano Monni and Mahlet Tadesse
introduce a stochastic partitioning method
that permits some covariates to affect
some response variables and not others,
and clusters responses which have
similar dependence on the same set of
covariates. Naturally, a clever MCMC
algorithm is employed, and the entire
process is illustrated on both simulated
and real genomic data. The paper is
accompanied by no fewer than four
invited discussions (by
Chipman/George/McCulloch,
Fraley, Li, and Stern) and rejoinder by
the authors.
In addition, the September 2009 issue
also features 7 other fine articles, ranging
from applications (e.g., prediction of
pregnancy using a new joint model for
longitudinal and binary responses) to
foundations (a new axiomatic comparison
of Cox-Jaynes and de Finetti views of
Bayesian statistics).
We hope you will enjoy the issue, and as
always welcome your submissions at
http://ba.stat.cmu.edu/submit/
The September 2009 issue includes the
following articles:
2009, Volume 04, Number 03, pp. 413--630
* A Stochastic Partitioning
Method to Associate High-dimensional
Responses and
Covariates, by Stefano Monni and Mahlet
G. Tadesse, pp. 413 -
436, posted online 2009-04-15,
DOI:10.1214/09-BA416
+ Comment on Article by Monni and
Tadesse, by H. Chipman,
E. George and R. McCulloch,
pp. 437 - 438, posted
online 2009-08-25,
DOI:10.1214/09-BA416A
+ Comment on Article by
Monni and Tadesse, by
C. Fraley, pp. 439
-448, posted online 2009-08-25,
DOI:10.1214/09-BA416B
+ Comment on Article by
Monni and Tadesse, by H. Li,
pp. 449 - 452, posted
online 2009-08-25,
DOI:10.1214/09-BA416C
+ Comment on Article by
Monni and Tadesse, by
H. Stern, pp. 453 -
456, posted online 2009-08-25,
DOI:10.1214/09-BA416D
- Rejoinder, by Stefano
Monni and Mahlet G. Tadesse,
pp. 457 - 464, posted
online 2009-08-25,
DOI:10.1214/09-BA416REJ
* Bayesian Analysis for Emerging
Infectious Diseases, by
Chris P Jewell, Theodore
Kypraios, Peter Neal and Gareth
O. Roberts, pp. 465 - 498,
posted online 2009-05-22,
DOI:10.1214/09-BA417
* Flexible Univariate Continuous
Distributions, by Fernando
A. Quintana, Mark F.J.
Steel and Jose T.A.S. Ferreira,
pp. 497 - 522, posted
online 2009-06-10,
DOI:10.1214/09-BA418
* Prediction of Pregnancy: A Joint
Model for Longitudinal
and Binary Data, by Julie
Horrocks and Marianne J. van Den
Heuvel, pp. 523 - 538,
posted online 2009-06-25,
DOI:10.1214/09-BA419
* Efficient Utility-based Clustering
over High Dimensional
Partition Spaces, by Silvia
Liverani, Paul E. Anderson,
Kieron D. Edwards, Andrew
J. Millar and Jim Q. Smith,
pp. 539 - 572, posted
online 2009-08-11,
DOI:10.1214/09-BA420
* Nonparametric estimation of the
distribution function in
contingent valuation
models, by David S. Leslie, Robert
Kohn and Denzil G. Fiebig,
pp. 573 - 598, posted online
2009-08-11,
DOI:10.1214/09-BA421
* New Axioms for Rigorous Bayesian
Probability, by Maurice
J. Dupre, and Frank J.
Tipler, pp. 599 - 606, posted
online 2009-08-11,
DOI:10.1214/09-BA422
* Bayes One-Sample and One-Way Random
Effects Analyses for
3-D Orientations with
Application to Materials Science, by
Melissa A. Bingham, Stephen
B. Vardeman and Daniel
J. Nordman, pp. 607 - 630,
posted online 2009-08-11,
DOI:10.1214/09-BA423
*****
The journal is sponsored by the
International Society for Bayesian
Analysis (ISBA). Its editors are Kate
Cowles, Philip Dawid, David
Dunson, David Heckerman, Michael Jordan,
Antonietta Mira, Fabrizio
Ruggeri and Bruno Sanso. Brad Carlin is
serving as Editor-in-Chief, Herbie Lee is
Managing Editor, Angelika van der Linde
is Production Editor, Marina
Vanucci is Deputy 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.
--
Heidi Rhodes Sestrich
Administrative Coordinator/
Document Production Specialist
Department of Statistics
Baker Hall 232A
Carnegie Mellon University
Pittsburgh, PA 15213
412-268-2718
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