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>.
| Version: | 0.3.4 | 
| Depends: | R (≥ 3.5.0) | 
| Suggests: | knitr, rmarkdown | 
| Published: | 2022-10-02 | 
| DOI: | 10.32614/CRAN.package.amanpg | 
| Author: | 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] | 
| Maintainer: | Zhong Zheng  <zvz5337 at psu.edu> | 
| License: | MIT + file LICENSE | 
| NeedsCompilation: | no | 
| Materials: | README | 
| CRAN checks: | amanpg results | 
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