varbvs: Variational inference for Bayesian variable selection

Implements the variational inference procedure for Bayesian variable selection, as described in the "Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies" (Bayesian Analysis 7, March 2012, pages 73-108). This software has been used to implement Bayesian variable selection for large problems with over a million variables and thousands of samples.

Version: 1.0
Suggests: grid, ggplot2
Published: 2012-04-10
Author: Peter Carbonetto
Maintainer: Peter Carbonetto <pcarbo at uchicago.edu>
License: GPL (≥ 3)
NeedsCompilation: yes
Citation: varbvs citation info
CRAN checks: varbvs results

Downloads:

Reference manual: varbvs.pdf
Package source: varbvs_1.0.tar.gz
OS X binary: varbvs_1.0.tgz
Windows binary: varbvs_1.0.zip