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 (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>.
Last updated 3 years ago
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6.89 score 32 stars 4 dependents 203 scripts 659 downloadsfunData - An S4 Class for Functional Data
S4 classes for univariate and multivariate functional data with utility functions. See <doi:10.18637/jss.v093.i05> for a detailed description of the package functionalities and its interplay with the MFPCA package for multivariate functional principal component analysis <https://CRAN.R-project.org/package=MFPCA>.
Last updated 1 years ago
6.15 score 14 stars 6 dependents 111 scripts 679 downloads