CRAN/E | ReMFPCA

ReMFPCA

Regularized Multivariate Functional Principal Component Analysis

Installation

About

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.

github.com/haghbinh/ReMFPCA

Key Metrics

Version 1.0.0
R ≥ 4.0
Published 2023-07-01 354 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks ReMFPCA results

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Maintainer

Maintainer

Hossein Haghbin

Authors

Hossein Haghbin

aut / cre

Yue Zhao

aut

Mehdi Maadooliat

aut

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Depends

R ≥ 4.0
R6

Imports

fda
expm
Matrix