Statistics Papers

Document Type

Journal Article

Date of this Version

2004

Publication Source

Statistical Science

Volume

19

Issue

1

Start Page

81

Last Page

94

DOI

10.1214/088342304000000035

Abstract

The evolution of Bayesian approaches for model uncertainty over the past decade has been remarkable. Catalyzed by advances in methods and technology for posterior computation, the scope of these methods has widened substantially. Major thrusts of these developments have included new methods for semiautomatic prior specification and posterior exploration. To illustrate key aspects of this evolution, the highlights of some of these developments are described.

Keywords

Bayes factors, classification and regression trees, model averaging, linear and nonparametric regression, objective prior distributions, reversible jump Markov chain Monte Carlo, variable selection

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Date Posted: 27 November 2017

This document has been peer reviewed.