vbsr: Variational Bayes Spike Regression Regularized Linear Models

Efficient algorithm for solving ultra-sparse regularized regression models using a variational Bayes algorithm with a spike (l0) prior. Algorithm is solved on a path, with coordinate updates, and is capable of generating very sparse models. There are very general model diagnostics for controling type-1 error included in this package.

Version:	0.0.5
Depends:	R (≥ 3.0.0)
Published:	2014-06-05
Author:	Benjamin Logsdon
Maintainer:	Benjamin Logsdon <ben.logsdon at sagebase.org>
License:	GPL-2
Copyright:	Benjamin Logsdon 2014
NeedsCompilation:	yes
CRAN checks:	vbsr results

Documentation:

Reference manual:	vbsr.pdf
Vignettes:	Using vbsr

Downloads:

Package source:	vbsr_0.0.5.tar.gz
Windows binaries:	r-devel: vbsr_0.0.5.zip, r-release: vbsr_0.0.5.zip, r-oldrel: vbsr_0.0.5.zip
macOS binaries:	r-release (arm64): vbsr_0.0.5.tgz, r-oldrel (arm64): vbsr_0.0.5.tgz, r-release (x86_64): vbsr_0.0.5.tgz, r-oldrel (x86_64): vbsr_0.0.5.tgz
Old sources:	vbsr archive

Reverse dependencies:

Reverse imports:

TraRe, trena

Linking:

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