VBsparsePCA: The Variational Bayesian Method for Sparse PCA

Contains functions for a variational Bayesian method for sparse PCA proposed by Ning (2020) <doi:10.48550/arXiv.2102.00305>. There are two algorithms: the PX-CAVI algorithm (if assuming the loadings matrix is jointly row-sparse) and the batch PX-CAVI algorithm (if without this assumption). The outputs of the main function, VBsparsePCA(), include the mean and covariance of the loadings matrix, the score functions, the variable selection results, and the estimated variance of the random noise.

Version: 0.1.0
Depends: R (≥ 3.6.0)
Imports: MASS, pracma, stats, utils
Published: 2021-02-12
DOI: 10.32614/CRAN.package.VBsparsePCA
Author: Bo (Yu-Chien) Ning
Maintainer: Bo (Yu-Chien) Ning <bo.ning at upmc.fr>
License: GPL-3
NeedsCompilation: no
CRAN checks: VBsparsePCA results


Reference manual: VBsparsePCA.pdf


Package source: VBsparsePCA_0.1.0.tar.gz
Windows binaries: r-devel: VBsparsePCA_0.1.0.zip, r-release: VBsparsePCA_0.1.0.zip, r-oldrel: VBsparsePCA_0.1.0.zip
macOS binaries: r-release (arm64): VBsparsePCA_0.1.0.tgz, r-oldrel (arm64): VBsparsePCA_0.1.0.tgz, r-release (x86_64): VBsparsePCA_0.1.0.tgz, r-oldrel (x86_64): VBsparsePCA_0.1.0.tgz

Reverse dependencies:

Reverse suggests: embed


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