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 (Happ & Greven, 2018) <doi:10.1080/01621459.2016.1273115>. Multivariate and univariate functional data objects are represented by S4 classes for this type of data implemented in the package 'funData'. For more details on the general concepts of both packages and a case study, see Happ-Kurz (2020) <doi:10.18637/jss.v093.i05>.
Version: 1.3-10 Depends: R (≥ 3.2.0), funData (≥ 1.3-4) Imports: abind, foreach, irlba, Matrix (≥ 1.5-0), methods, mgcv (≥ 1.8-33), plyr, stats Suggests: covr, fda, testthat (≥ 2.0.0) Published: 2022-09-15 DOI: 10.32614/CRAN.package.MFPCA Author: Clara Happ-Kurz [aut, cre] Maintainer: Clara Happ-Kurz <chk_R at gmx.de> License: GPL-2 URL: https://github.com/ClaraHapp/MFPCA NeedsCompilation: yes SystemRequirements: libfftw3 (>= 3.3.4) Citation: MFPCA citation info Materials: README NEWS In views: FunctionalData CRAN checks: MFPCA results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=MFPCA to link to this page.
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