Journal
STATISTICAL SCIENCE
Volume 19, Issue 1, Pages 81-94Publisher
INST MATHEMATICAL STATISTICS
DOI: 10.1214/088342304000000035
Keywords
Bayes factors; classification and regression trees; model averaging; linear and nonparametric regression; objective prior distributions; reversible jump Markov chain Monte Carlo; variable selection
Categories
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available
Share Paper
