VIGoR: Variational Bayesian Inference for Genome-Wide Regression

Conducts linear regression using variational Bayesian inference, particularly optimized for genome-wide association mapping and whole-genome prediction which use a number of DNA markers as the explanatory variables. Provides seven regression models which select the important variables (i.e., the variables related to response variables) among the given explanatory variables in different ways (i.e., model structures).

Version: 1.0
Published: 2015-05-20
Author: Akio Onogi and Hiroyoshi Iwata
Maintainer: Akio Onogi <onogiakio at>
License: MIT + file LICENSE
NeedsCompilation: yes
CRAN checks: VIGoR results


Reference manual: VIGoR.pdf
Package source: VIGoR_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: VIGoR_1.0.tgz
OS X Mavericks binaries: r-oldrel: VIGoR_1.0.tgz


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