BAS: Bayesian Model Averaging using Bayesian Adaptive Sampling

Package for Bayesian Model Averaging in linear models using stochastic or deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner's g-prior or mixtures of g-priors corresponding to the Zellner-Siow Cauchy Priors or the Liang et al hyper-g priors (JASA 2008). Other model selection criterian include AIC and BIC. Sampling probabilities may be updated based on the sampled models. Allows uniform or beta-binomial prior distributions on models.

Version: 1.0
Depends: R (≥ 2.15), stats, MASS
Imports: stats
Published: 2012-06-01
Author: Merlise Clyde with contributions from Michael Littman amd Joyee Ghosh
Maintainer: Merlise Clyde <clyde at stat.duke.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.r-project.org, http://www.stat.duke.edu/~clyde/BAS
NeedsCompilation: yes
Materials: ChangeLog
In views: Bayesian
CRAN checks: BAS results

Downloads:

Reference manual: BAS.pdf
Package source: BAS_1.0.tar.gz
MacOS X binary: BAS_1.0.tgz
Windows binary: BAS_1.0.zip
Old sources: BAS archive