EESPCA-package

<p>Implementation of Eigenvectors from Eigenvalues Sparse Principal Component Analysis (EESPCA).</p>

 package

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>.

H Robert Frost

Package:	EESPCA
Type:	Package
Version:	0.7.0
Date:	2021
License:	GPL-2

EESPCA-package: Eigenvectors

Description

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Details

References