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) . Zou, H., Hastie, T., & Tibshirani, R. (2006) . Zou, H., & Xue, L. (2018) .


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install.packages("amanpg")

0.3.3 by Lingzhou Xue, 16 days ago


Browse source code at https://github.com/cran/amanpg


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


Documentation:   PDF Manual  


MIT + file LICENSE license


Suggests knitr, rmarkdown


See at CRAN