MFPCA: Multivariate Functional Principal Component Analysis for Data Observed on Different Dimensional Domains

Calculate a multivariate functional principal component analysis for data observed on different dimensional domains. The estimation algorithm relies on univariate basis expansions for each element of the multivariate functional data. Multivariate and univariate functional data objects are represented by S4 classes for this type of data implemented in the package 'funData'.

Version: 1.1
Depends: R (≥ 3.1.0), funData
Imports: abind, foreach, irlba, Matrix, methods, mgcv, plyr, stats
Suggests: covr, testthat
Published: 2017-06-17
Author: Clara Happ [aut, cre]
Maintainer: Clara Happ <clara.happ at stat.uni-muenchen.de>
License: GPL-2
NeedsCompilation: yes
SystemRequirements: libfftw3 (>= 3.3.4)
Citation: MFPCA citation info
Materials: README NEWS
In views: FunctionalData
CRAN checks: MFPCA results

Downloads:

Reference manual: MFPCA.pdf
Package source: MFPCA_1.1.tar.gz
Windows binaries: r-devel: MFPCA_1.1.zip, r-release: MFPCA_1.1.zip, r-oldrel: MFPCA_1.1.zip
OS X El Capitan binaries: r-release: MFPCA_1.1.tgz
OS X Mavericks binaries: r-oldrel: MFPCA_1.1.tgz
Old sources: MFPCA archive

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