Package: msma
Type: Package
Title: Multiblock Sparse Multivariable Analysis
Version: 4.0
Authors@R: person("Atsushi", "Kawaguchi", role = c("aut", "cre"), email = "kawa_a24@yahoo.co.jp")
Depends: R (>= 3.5)
Description: Several functions can be used to analyze multiblock
        multivariable data. If the input is a single matrix, then
        principal components analysis (PCA) is implemented. If the
        input is a list of matrices, then multiblock PCA is
        implemented. If the input is two matrices, for exploratory and
        objective variables, then partial least squares (PLS) analysis
        is implemented. If the input is two lists of matrices, for
        exploratory and objective variables, then multiblock PLS
        analysis is implemented. Additionally, if an extra outcome
        variable is specified, then a supervised version of the methods
        above is implemented. For each method, sparse modeling is also
        incorporated. Functions for selecting the number of components
        and regularized parameters are also provided. Version 4.0 adds
        opt-in supervised sparse soft-structured principal component
        analysis, reconstruction, and repeated split
        reconstruction-based parameter selection while preserving the
        default Version 3.2 computational paths.
License: GPL (>= 2)
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Config/testthat/edition: 3
Packaged: 2026-10-03 08:30:53 UTC; root
Author: Atsushi Kawaguchi [aut, cre]
Maintainer: Atsushi Kawaguchi <kawa_a24@yahoo.co.jp>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-10-03 02:30:02 UTC
RemoteUrl: https://github.com/cran/msma
RemoteRef: HEAD
RemoteSha: 23616c10445d35a8c1a25f2e3544e0a074392991
