Package: amanpg 0.3.4

Zhong Zheng

amanpg: Alternating Manifold Proximal Gradient Method for Sparse PCA

Alternating Manifold Proximal Gradient Method for Sparse PCA uses the Alternating Manifold Proximal Gradient (AManPG) method to find sparse principal components from a data or covariance matrix. Provides a novel algorithm for solving the sparse principal component analysis problem which provides advantages over existing methods in terms of efficiency and convergence guarantees. Chen, S., Ma, S., Xue, L., & Zou, H. (2020) <doi:10.1287/ijoo.2019.0032>. Zou, H., Hastie, T., & Tibshirani, R. (2006) <doi:10.1198/106186006X113430>. Zou, H., & Xue, L. (2018) <doi:10.1109/JPROC.2018.2846588>.

Authors:Shixiang Chen [aut], Justin Huang [aut], Benjamin Jochem [aut], Shiqian Ma [aut], Haichuan Xu [aut], Lingzhou Xue [aut], Zhong Zheng [cre, aut], Hui Zou [aut]

amanpg_0.3.4.tar.gz
amanpg_0.3.4.tar.gz(r-4.5-noble)amanpg_0.3.4.tar.gz(r-4.4-noble)
amanpg_0.3.4.tgz(r-4.4-emscripten)amanpg_0.3.4.tgz(r-4.3-emscripten)
amanpg.pdf |amanpg.html✨
amanpg/json (API)

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

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 3 scripts 293 downloads 3 exports 0 dependencies

Last updated 2 years agofrom:345b3cf6d1. Checks:OK: 1 WARNING: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 09 2024
R-4.5-linuxWARNINGNov 09 2024

Exports:normalizeprox.l1spca.amanpg

Dependencies:

An Introduction to amanpg

Shixiang Chen, Justin Huang, Benjamin Jochem, Lingzhou Xue, Hui Zou

Rendered fromAn-Introduction-to-amanpg.Rmdusingknitr::rmarkdownon Nov 09 2024.

Last update: 2021-10-02
Started: 2021-10-02