funpca: Functional Principal Component Analysis

Functional principal component analysis under the Linear Mixed Models representation of smoothing splines. The method utilizes the Demmler-Reinsch basis and assumes error independence. For more details see: F. Rosales (2016) <https://ediss.uni-goettingen.de/handle/11858/00-1735-0000-0028-87F9-6>.

Version: 9.0
Depends: Brobdingnag, MASS, nlme, fda
Published: 2023-06-15
DOI: 10.32614/CRAN.package.funpca
Author: Francisco Rosales [aut, cph, cre], Tatyana Krivobokova [con, ths]
Maintainer: Francisco Rosales <francisco.rosales-marticorena at protonmail.com>
License: GPL-2
NeedsCompilation: no
CRAN checks: funpca results

Documentation:

Reference manual: funpca.pdf

Downloads:

Package source: funpca_9.0.tar.gz
Windows binaries: r-devel: funpca_9.0.zip, r-release: funpca_9.0.zip, r-oldrel: funpca_9.0.zip
macOS binaries: r-release (arm64): funpca_9.0.tgz, r-oldrel (arm64): funpca_9.0.tgz, r-release (x86_64): funpca_9.0.tgz, r-oldrel (x86_64): funpca_9.0.tgz

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