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: 1.2
Depends: R (≥ 3.1.0), funData (≥ 1.2)
Imports: abind, foreach, irlba, Matrix, methods, mgcv, plyr, stats
Suggests: covr, testthat
Published: 2018-02-22
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
CRAN checks: MFPCA results

Downloads:

Reference manual: MFPCA.pdf
Package source: MFPCA_1.2.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
OS X El Capitan binaries: r-release: not available
OS X Mavericks binaries: r-oldrel: not available
Old sources: MFPCA archive

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