Eigenvectors from Eigenvalues Sparse Principal Component Analysis (EESPCA)

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Documentation for package ‘EESPCA’ version 0.7.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

EESPCA-package	Eigenvectors
computeApproxNormSquaredEigenvector	Approximates the normed squared eigenvector loadings
computeResidualMatrix	Calculates the residual matrix from the reduced rank reconstruction
eespca	Eigenvectors from Eigenvalues Sparse Principal Component Analysis (EESPCA)
eespcaCV	Cross-validation for Eigenvectors from Eigenvalues Sparse Principal Component Analysis (EESPCA)
eespcaForK	Multi-PC version of Eigenvectors from Eigenvalues Sparse Principal Component Analysis (EESPCA)
powerIteration	Power iteration method for calculating principal eigenvector and eigenvalue.
reconstruct	Calculates the reduced rank reconstruction
reconstructionError	Calculates the reduced rank reconstruction error
rifleInit	Computes the initial eigenvector for the rifle method of Tan et al.
riflePCACV	Sparsity parameter selection via cross-validation for rifle method of Tan et al.
tpower	Implementation of the Yuan and Zhang TPower method.
tpowerPCACV	Sparsity parameter selection for the Yuan and Zhang TPower method using cross-validation.