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:

Some CRAN statistics:

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')