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VBsparsePCA  

The Variational Bayesian Method for Sparse PCA
View on CRAN: Click here


Download and install VBsparsePCA package within the R console
Install from CRAN:
install.packages("VBsparsePCA")

Install from Github:
library("remotes")
install_github("cran/VBsparsePCA")

Install by package version:
library("remotes")
install_version("VBsparsePCA", "0.1.0")



Attach the package and use:
library("VBsparsePCA")
Maintained by
Bo (Yu-Chien) Ning
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-12
Latest Update: 2021-02-12
Description:
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.
How to cite:
Bo (Yu-Chien) Ning (2021). VBsparsePCA: The Variational Bayesian Method for Sparse PCA. R package version 0.1.0, https://cran.r-project.org/web/packages/VBsparsePCA. Accessed 25 Jun. 2026.
Previous versions and publish date:
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Complete documentation for VBsparsePCA
Functions, R codes and Examples using the VBsparsePCA R package
Some associated functions: VBsparsePCA . foldednorm.mean . spca.cavi.Laplace . spca.cavi.mvn . 
Some associated R codes: PX-CAVI-Laplace.R . PX-CAVI-MVN.R . VBsparsePCA.R . foldednormalmean.R .  Full VBsparsePCA package functions and examples
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