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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 suggests: | embed |
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