<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Multivariate Functional Principal Component Analysis for Data
Observed on Different Dimensional Domains</dc:title>
  <dc:title>R package MFPCA version 1.3-11</dc:title>
  <dc:subject>CRAN Task View: FunctionalData (https://CRAN.R-project.org/view=FunctionalData)</dc:subject>
  <dc:description>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 &amp; Greven, 2018) &lt;doi:10.1080/01621459.2016.1273115&gt;. 
    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) &lt;doi:10.18637/jss.v093.i05&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 3.2.0), funData (&gt;= 1.3-4)</dc:relation>
  <dc:relation>Imports: abind, foreach, irlba, Matrix(&gt;= 1.5-0), methods, mgcv (&gt;=
1.8-33), plyr, stats</dc:relation>
  <dc:relation>Suggests: covr, fda, testthat (&gt;= 2.0.0)</dc:relation>
  <dc:creator>Clara Happ-Kurz &lt;chk_R@gmx.de&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Clara Happ-Kurz [aut, cre] (ORCID:
    &lt;https://orcid.org/0000-0003-4737-3835&gt;)</dc:contributor>
  <dc:rights>GPL-2</dc:rights>
  <dc:date>2025-08-27</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=MFPCA</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.MFPCA</dc:identifier>
</oai_dc:dc>
