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: 1.0-1
Depends: R (≥ 3.1.0), funData
Imports: abind, foreach, irlba, Matrix, methods, mgcv, plyr, stats
Suggests: testthat
Published: 2016-08-12
Author: Clara Happ [aut, cre]
Maintainer: Clara Happ <clara.happ at>
License: GPL-2
NeedsCompilation: yes
SystemRequirements: libfftw3 (>= 3.3.4)
Citation: MFPCA citation info
CRAN checks: MFPCA results


Reference manual: MFPCA.pdf
Package source: MFPCA_1.0-1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: MFPCA_1.0-1.tgz, r-oldrel: MFPCA_1.0-1.tgz
Old sources: MFPCA archive


Please use the canonical form to link to this page.