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November 2012 Bayesian statistics with a smile: A resampling–sampling perspective
Hedibert F. Lopes, Nicholas G. Polson, Carlos M. Carvalho
Braz. J. Probab. Stat. 26(4): 358-371 (November 2012). DOI: 10.1214/11-BJPS144

Abstract

In this paper we develop a simulation-based approach to sequential inference in Bayesian statistics. Our resampling–sampling perspective provides draws from posterior distributions of interest by exploiting the sequential nature of Bayes theorem. Predictive inferences are a direct byproduct of our analysis as are marginal likelihoods for model assessment. We illustrate our approach in a hierarchical normal-means model and in a sequential version of Bayesian lasso. This approach provides a simple yet powerful framework for the construction of alternative posterior sampling strategies for a variety of commonly used models.

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Hedibert F. Lopes. Nicholas G. Polson. Carlos M. Carvalho. "Bayesian statistics with a smile: A resampling–sampling perspective." Braz. J. Probab. Stat. 26 (4) 358 - 371, November 2012. https://doi.org/10.1214/11-BJPS144

Information

Published: November 2012
First available in Project Euclid: 3 July 2012

zbMATH: 1319.62062
MathSciNet: MR2949084
Digital Object Identifier: 10.1214/11-BJPS144

Rights: Copyright © 2012 Brazilian Statistical Association

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Vol.26 • No. 4 • November 2012
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