nipals: Principal Components Analysis using NIPALS or Weighted EMPCA, with Gram-Schmidt Orthogonalization

Principal Components Analysis of a matrix using Non-linear Iterative Partial Least Squares or weighted Expectation Maximization PCA with Gram-Schmidt orthogonalization of the scores and loadings. Optimized for speed. See Andrecut (2009) <doi:10.1089/cmb.2008.0221>.

Version: 0.8
Depends: R (≥ 3.4.0)
Suggests: knitr, rmarkdown, testthat
Published: 2021-09-15
DOI: 10.32614/CRAN.package.nipals
Author: Kevin Wright ORCID iD [aut, cre]
Maintainer: Kevin Wright <kw.stat at>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
In views: MissingData
CRAN checks: nipals results


Reference manual: nipals.pdf
Vignettes: EMPCA notes
NIPALS algorithm
Comparing results and performance of NIPALS functions in R
NIPALS optimization notes


Package source: nipals_0.8.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): nipals_0.8.tgz, r-oldrel (arm64): nipals_0.8.tgz, r-release (x86_64): nipals_0.8.tgz, r-oldrel (x86_64): nipals_0.8.tgz
Old sources: nipals archive

Reverse dependencies:

Reverse imports: areabiplot, gge, powerPLS, scp
Reverse suggests: pRoloc


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