Package: EESPCA
Type: Package
Title: Eigenvectors from Eigenvalues Sparse Principal Component
        Analysis (EESPCA)
Version: 0.7.0
Author: H. Robert Frost
Maintainer: H. Robert Frost <rob.frost@dartmouth.edu>
Description: Contains logic for computing sparse principal components via the EESPCA method, 
    which is based on an approximation of the eigenvector/eigenvalue identity. 
    Includes logic to support execution of the TPower and rifle sparse PCA methods,
    as well as logic to estimate the sparsity parameters used by EESPCA, TPower and rifle
    via cross-validation to minimize the out-of-sample reconstruction error.
    H. Robert Frost (2021) <doi:10.1080/10618600.2021.1987254>.
Depends: R (>= 3.6.0), rifle (>= 1.0.0), MASS, PMA
License: GPL (>= 2)
Copyright: Dartmouth College
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-06-15 19:58:05 UTC; d37329b
Repository: CRAN
Date/Publication: 2022-06-15 20:10:02 UTC
Built: R 4.3.3; ; 2025-01-24 15:37:21 UTC; unix
