The BAS
R package is designed to
provide an easy to use package and fast code for implementing Bayesian Model
Averaging and Model Selection in R using state of the art prior
distributions for linear and generalized linear models. All of the
prior distributions in BAS
are based on Zellner's g-prior or
mixtures of g-priors. These have been shown to be consistent and have
a number of computational advantages. BAS implements two main
algorithms for sampling from the space of potential models: an
adaptive sampling without replacement algorithm and a MCMC algorithm
that utilizes swapping to escape from local modes. More details are
in the R man pages.
Current build and test coverage status:
The stable version can be installed easily in the R
console like any other package:
install.packages('BAS')
On the other hand, I welcome everyone to use the most recent version
of the package with quick-fixes, new features and probably new
bugs. It's currently hosted on
GitHub. To get the latest
development version from GitHub,
use the devtools
package from
CRAN and enter in R
:
devtools::install_github('merliseclyde/BAS')