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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "EESPCA" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'EESPCA: Eigenvectors from Eigenvalues Sparse Principal Component Analysis
  (EESPCA)'
version: 0.8.0
doi: 10.32614/CRAN.package.EESPCA
abstract: 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) <https://doi.org/10.1080/10618600.2021.1987254>.
authors:
- family-names: Frost
  given-names: H. Robert
  email: rob.frost@dartmouth.edu
repository: https://hrobertfrost.r-universe.dev
commit: 95bba92619af4faf61edefe63d02ad969ef26964
date-released: '2025-07-21'
contact:
- family-names: Frost
  given-names: H. Robert
  email: rob.frost@dartmouth.edu