Package: VBsparsePCA 0.1.0

Bo (Yu-Chien) Ning

VBsparsePCA: The Variational Bayesian Method for Sparse PCA

Contains functions for a variational Bayesian method for sparse PCA proposed by Ning (2020) <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.

Authors:Bo Ning

VBsparsePCA_0.1.0.tar.gz
VBsparsePCA_0.1.0.zip(r-4.7-any)VBsparsePCA_0.1.0.zip(r-4.6-any)VBsparsePCA_0.1.0.zip(r-4.5-any)
VBsparsePCA_0.1.0.tgz(r-4.6-any)VBsparsePCA_0.1.0.tgz(r-4.5-any)
VBsparsePCA_0.1.0.tar.gz(r-4.7-any)VBsparsePCA_0.1.0.tar.gz(r-4.6-any)
VBsparsePCA_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
VBsparsePCA/json (API)

# Install 'VBsparsePCA' in R:
install.packages('VBsparsePCA', repos = c('https://yc-ning.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yc-ning/vbsparsepca/issues

On CRAN:

Conda:

2.70 score 280 downloads 4 exports 2 dependencies

Last updated from:019b82aec9. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE88
source / vignettesOK183
linux-releaseNOTE90
macos-releaseNOTE157
macos-oldrelNOTE204
windows-develNOTE55
windows-releaseNOTE56
windows-oldrelNOTE63
wasm-releaseOK69

Exports:foldednorm.meanspca.cavi.Laplacespca.cavi.mvnVBsparsePCA

Dependencies:MASSpracma