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MFPCA  

Multivariate Functional Principal Component Analysis for Data Observed on Different Dimensional Domains
View on CRAN: Click here


Download and install MFPCA package within the R console
Install from CRAN:
install.packages("MFPCA")

Install from Github:
library("remotes")
install_github("cran/MFPCA")

Install by package version:
library("remotes")
install_version("MFPCA", "1.3-11")



Attach the package and use:
library("MFPCA")
Maintained by
Clara Happ-Kurz
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-07-22
Latest Update: 2025-09-01
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 & Greven, 2018) . 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) .
How to cite:
Clara Happ-Kurz (2016). MFPCA: Multivariate Functional Principal Component Analysis for Data Observed on Different Dimensional Domains. R package version 1.3-11, https://cran.r-project.org/web/packages/MFPCA. Accessed 30 Oct. 2026.
Previous versions and publish date:
1.0-1 (2016-08-12 12:36), 1.0 (2016-07-22 19:29), 1.1 (2017-06-17 16:35), 1.2-2 (2018-05-25 18:00), 1.2-3 (2018-07-03 15:30), 1.2 (2018-02-22 18:31), 1.3-1 (2018-10-04 13:20), 1.3-2 (2019-03-21 00:13), 1.3-4 (2020-01-08 10:30), 1.3-5 (2020-04-25 20:00), 1.3-6 (2020-09-04 07:12), 1.3-8 (2021-08-09 09:50), 1.3-9 (2021-10-17 19:00), 1.3-10 (2022-09-15 10:30), 1.3 (2018-08-13 20:00), (2026-07-09 08:09)
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Complete documentation for MFPCA
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