Package: ReMFPCA
Type: Package
Title: Regularized Multivariate Functional Principal Component Analysis
Version: 2.0.0
Authors@R: c(
    person("Hossein", "Haghbin", email = "haghbin@pgu.ac.ir", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8416-2354")),
    person("Yue", "Zhao", email = "yue.zhao@mu.edu", role = "aut", comment = c(ORCID = "0009-0000-4561-9163")),
    person("Mehdi", "Maadooliat", email = "mehdi.maadooliat@mu.edu", role = "aut", comment = c(ORCID = "0000-0002-5408-2676"))
    )
Maintainer: Hossein Haghbin <haghbin@pgu.ac.ir>
Description: Methods and tools for implementing regularized multivariate functional principal component analysis ('ReMFPCA') for multivariate functional data whose variables might be observed over different dimensional domains. 'ReMFPCA' is an object-oriented interface leveraging the extensibility and scalability of R6. It employs a parameter vector to control the smoothness of each functional variable. By incorporating smoothness constraints as penalty terms within a regularized optimization framework, 'ReMFPCA' generates smooth multivariate functional principal components, offering a concise and interpretable representation of the data. For detailed information on the methods and techniques used in 'ReMFPCA', please refer to Haghbin et al. (2023) <doi:10.48550/arXiv.2306.13980>. 
URL: https://github.com/haghbinh/ReMFPCA
License: GPL (>= 2)
Encoding: UTF-8
LazyData: TRUE
Imports: fda, expm, Matrix
RoxygenNote: 7.3.2
Depends: R (>= 4.0), R6
NeedsCompilation: no
Packaged: 2025-04-12 08:31:33 UTC; Haghbin
Author: Hossein Haghbin [aut, cre] (<https://orcid.org/0000-0001-8416-2354>),
  Yue Zhao [aut] (<https://orcid.org/0009-0000-4561-9163>),
  Mehdi Maadooliat [aut] (<https://orcid.org/0000-0002-5408-2676>)
Repository: CRAN
Date/Publication: 2025-04-12 08:50:02 UTC
Built: R 4.7.0; ; 2026-06-12 03:46:08 UTC; windows
