JSM 2004 - Toronto

Abstract #302252

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Activity Number: 168
Type: Other
Date/Time: Tuesday, August 10, 2004 : 8:30 AM to 10:20 AM
Sponsor: ASA
Abstract - #302252
Title: Applied Bayesian Data Analysis
Author(s): Andrew Gelman*+
Companies: Columbia University
Address: Dept. of Statistics, New York, NY, 10027,
Keywords:
Abstract:

Computational developments over the past 20 years have accompanied a resurgence of interest in Bayesian methodology which, though once the dominating paradigm, had lain almost dormant for much of the last century. We introduce modern Bayesian computational methods, starting with the Gibbs sampler and the Metropolis algorithms that improve simulation efficiency. We discuss the theoretical and practical issues of implementation and illustrate with a series of examples of Bayesian inference in our applied research in biology and the social sciences.

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Revised March 2004