RMLPCA: Maximum Likelihood Principal Component Analysis

R implementation of Maximum Likelihood Principal Component Analysis The main idea of this package is to have an alternative way of PCA for subspace modeling that considers measurement errors. More details can be found in Peter D. Wentzell (2009) <doi:10.1016/B978-0-444-64165-6.03029-9>.

Version: 0.0.1
Depends: R (≥ 2.10)
Imports: base, Matrix, pracma, RSpectra
Suggests: testthat, knitr, rmarkdown
Published: 2020-11-05
Author: Renan Santos Barbosa [aut, cre]
Maintainer: Renan Santos Barbosa <renansantosbarbosa at usp.br>
BugReports: https://github.com/renanestatcamp/RMLPCA/issues
License: MIT + file LICENSE
URL: https://github.com/renanestatcamp/RMLPCA
NeedsCompilation: no
Materials: README NEWS
CRAN checks: RMLPCA results

Downloads:

Reference manual: RMLPCA.pdf
Package source: RMLPCA_0.0.1.tar.gz
Windows binaries: r-devel: RMLPCA_0.0.1.zip, r-release: RMLPCA_0.0.1.zip, r-oldrel: RMLPCA_0.0.1.zip
macOS binaries: r-release (arm64): RMLPCA_0.0.1.tgz, r-release (x86_64): RMLPCA_0.0.1.tgz, r-oldrel: RMLPCA_0.0.1.tgz

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