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We develop a coherent framework for integrative simultaneous analysis of the explorationexploitation and model order selection tradeoffs. We improve over our preceding results on the same subject ...
We define a conjugate prior for the reversible Markov chain of order r. The prior arises from a partially exchangeable reinforced random walk, in the same way that the Beta distribution arises from ...
We present two alternative ways to apply PAC-Bayesian analysis to sequences of dependent random variables. The first is based on a new lemma that enables to bound expectations of convex functions of...
This paper presents a study of the large-sample behavior of the posterior distribution of a structural parameter which is partially identified by moment inequalities. The posterior density is derive...
Infectious diseases both within human and animal populations often pose serious health and socioeconomic risks. From a statistical perspective, their prediction is complicated by the fact...
Bayesian analysis incorporates different sources of information into a single analysis through Bayes theorem.When one or more of the sources of information are suspect(e.g.,if the model assumed for ...
In this article,we present a behind-the-scenes look at a Bayesian hierarchical analysis of pathways of exposure to arsenic(a toxic heavy metal) using the Phase I National Human Exposure Assessment ...
A major challenge to the statistical analysis of microarray data is the small number of samples limited by both cost and sample availability compared to the large number of genes, now soaring into t...
In this contribution to the discussion of Th case for objective Bayesian analysis by James Berger and Sujective Bayesian analysis: princi- ples and practice by Michael Goldstein, I argue that (a) al...
We address the position of subjectivism within Bayesian statistics. We argue, rst, that the subjectivist Bayes approach is the only feasible method for tackling many important practical problems. Se...
Bayesian statistical practice makes extensive use of versions of ob- jective Bayesian analysis. We discuss why this is so, and address some of the criticisms that have been raised concerning objecti...
For Bayesian analysis of massive data, Markov chain Monte Carlo (MCMC) techniques often prove infeasible due to computational resource constraints. Standard MCMC methods generally require a complete s...
Bayesian Analysis is an electronic journal of the International Society for Bayesian Analysis. It seeks to publish a wide range of articles that demonstrate or discuss Bayesian methods in some theoret...
Bayesian Analysis is an electronic journal of the International Society for Bayesian Analysis. It seeks to publish a wide range of articles that demonstrate or discuss Bayesian methods in some theoret...
In this paper we consider a Bayesian analysis of contingency tables allowing for the possibility that cells may have probability zero. In this sense we depart from standard log-linear modeling that ...

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