Nothing
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>.
Getting started
Browse package contents
Package details |
|
|---|---|
| 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@psu.edu> |
| License | MIT + file LICENSE |
| Version | 0.3.4 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the amanpg package in your browser
Any scripts or data that you put into this service are public.
