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.
- Version0.3.4
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Chen, S., Ma, S., Xue, L., & Zou, H. (2020)
- Zou, H., Hastie, T., & Tibshirani, R. (2006)
- Zou, H., & Xue, L. (2018)
- Last release10/02/2022
Documentation
Team
Zhong Zheng
Hui Zou
Show author detailsRolesAuthorLingzhou Xue
Show author detailsRolesAuthorShixiang Chen
Show author detailsRolesAuthorJustin Huang
Show author detailsRolesAuthorBenjamin Jochem
Show author detailsRolesAuthorShiqian Ma
Show author detailsRolesAuthorHaichuan Xu
Show author detailsRolesAuthor
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