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


Reference manual: vbsr.pdf
Vignettes: Using vbsr


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

Reverse dependencies:

Reverse imports: TraRe, trena


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