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DESCRIPTION
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DESCRIPTION
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Package: BAS
Version: 1.0.5
Date: 2015-7-15
Title: Bayesian Model Averaging using Bayesian Adaptive Sampling
Author: Merlise Clyde <clyde@stat.duke.edu> with contributions from
Michael Littman, Quanli Wang, Joyee Ghosh, Yingbo Li
Authors@R: c(person("Merlise", "Clyde", email="clyde@stat.duke.edu",
role=c("aut","cre", "cph")),
person("Michael", "Littman", role="ctb"),
person("Quanli", "Wang", role="ctb"),
person("Joyee", "Ghosh", role="ctb"),
person("Yingbo", "Li", role="ctb"))
Maintainer: Merlise Clyde <clyde@stat.duke.edu>
Depends: R (>= 3.0)
Suggests: MASS
Description: Package for Bayesian Model Averaging in linear models and
generalized 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) or mixtures of
g-priors in GLMS of Li and Clyde 2015. Other model
selection criterian include AIC and BIC. Sampling
probabilities may be updated based on the sampled models
using Sampleing w/out Replacement or an MCMC algorithm
samples models using the BAS tree structure as an efficient
hash table. Allows uniform or beta-binomial prior distributions on
models, and may force varialbes to allways be included.
License: GPL (>= 2)
URL: http://www.r-project.org, http://www.stat.duke.edu/~clyde/BAS
Packaged: 2012-05-31 19:26:40 UTC; clyde
Repository: CRAN
NeedsCompilation: yes