Package: amanpg
Version: 0.3.1
Date: 2021-08-21
Title: Alternating Manifold Proximal Gradient Method for Sparse PCA
Type: Package
Authors@R: c(
    person("Shixiang", "Chen", role = "aut"),
    person("Justin", "Huang", role = "aut"),
    person("Benjamin","Jochem", role = "aut"),
    person("Shiqian", "Ma", role = "aut"),
    person("Lingzhou", "Xue", email = "lzxue@psu.edu", role = c("cre","aut")),
    person("Hui", "Zou", role = "aut"))
Description: 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>.
License: MIT + file LICENSE
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-09-01 15:00:55 UTC; benjochem
Author: Shixiang Chen [aut],
  Justin Huang [aut],
  Benjamin Jochem [aut],
  Shiqian Ma [aut],
  Lingzhou Xue [cre, aut],
  Hui Zou [aut]
Maintainer: Lingzhou Xue <lzxue@psu.edu>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-09-02 11:00:10 UTC
