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:
VBsparsePCA_0.1.0.tar.gz
VBsparsePCA_0.1.0.zip(r-4.5)VBsparsePCA_0.1.0.zip(r-4.4)VBsparsePCA_0.1.0.zip(r-4.3)
VBsparsePCA_0.1.0.tgz(r-4.4-any)VBsparsePCA_0.1.0.tgz(r-4.3-any)
VBsparsePCA_0.1.0.tar.gz(r-4.5-noble)VBsparsePCA_0.1.0.tar.gz(r-4.4-noble)
VBsparsePCA_0.1.0.tgz(r-4.4-emscripten)VBsparsePCA_0.1.0.tgz(r-4.3-emscripten)
VBsparsePCA.pdf |VBsparsePCA.html✨
VBsparsePCA/json (API)
| # Install 'VBsparsePCA' in R: |
| install.packages('VBsparsePCA', repos = c('https://bo-ning.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bo-ning/vbsparsepca/issues
Last updated 4 years agofrom:019b82aec9. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 05 2024 |
| R-4.5-win | NOTE | Nov 05 2024 |
| R-4.5-linux | NOTE | Nov 05 2024 |
| R-4.4-win | NOTE | Nov 05 2024 |
| R-4.4-mac | NOTE | Nov 05 2024 |
| R-4.3-win | NOTE | Nov 05 2024 |
| R-4.3-mac | NOTE | Nov 05 2024 |
Exports:foldednorm.meanspca.cavi.Laplacespca.cavi.mvnVBsparsePCA
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| The function for obtaining the mean of a folded normal distribution | foldednorm.mean |
| Function for the PX-CAVI algorithm using the Laplace slab | spca.cavi.Laplace |
| Function for the PX-CAVI algorithm using the multivariate normal slab | spca.cavi.mvn |
| The main function for the variational Bayesian method for sparse PCA | VBsparsePCA |