Package: fastPLS
Type: Package
Title: Fast Partial Least Squares for High-Dimensional Data
Version: 0.99.3
Date: 2026-07-05
Authors@R: c(person("Stefano", "Cacciatore", role = c("aut", "cre"),email = "stefano.cacciatore@icgeb.org", comment = c(ORCID = "0000-0001-7052-7156")),
             person("Dupe", "Ojo", role = "aut",email = "dupe.ojo@icgeb.org", comment = c(ORCID = "0000-0002-5301-8592")),
             person("Leonardo", "Tenori", role = "aut",email = "tenori@cerm.unifi.it", comment = c(ORCID = "0000-0001-6438-059X")),
             person("Alessia", "Vignoli", role = "aut",email = "vignoli@cerm.unifi.it", comment = c(ORCID = "0000-0003-4038-6596")))
Author: Stefano Cacciatore [aut, cre]
        (<https://orcid.org/0000-0001-7052-7156>), Dupe Ojo [aut]
        (<https://orcid.org/0000-0002-5301-8592>), Leonardo Tenori
        [aut] (<https://orcid.org/0000-0001-6438-059X>), Alessia
        Vignoli [aut] (<https://orcid.org/0000-0003-4038-6596>)
Maintainer: Stefano Cacciatore <stefano.cacciatore@icgeb.org>
Description: Fast implementations of partial least squares models for
        high-dimensional regression and classification. The package
        provides compiled implementations of PLS-SVD, SIMPLS, OPLS and
        kernel PLS, together with truncated singular value
        decomposition backends, discriminant classifiers,
        cross-validation utilities and optional CUDA or Apple Metal
        acceleration when the required system libraries are available.
License: GPL-3
URL: https://github.com/tkcaccia/fastPLS
BugReports: https://github.com/tkcaccia/fastPLS/issues
biocViews: Software, DimensionReduction, Classification, Regression,
        GeneExpression, Metabolomics, SingleCell, GPU
SystemRequirements: Optional CUDA Toolkit and NVIDIA GPU driver for
        CUDA acceleration; optional Apple Metal framework on macOS for
        Metal acceleration. CPU-only builds do not require GPU
        software.
Depends: R (>= 4.5.0), Matrix
Imports: Rcpp (>= 0.12.17), methods, float
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, Matrix
Suggests: BiocStyle, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Config/testthat/edition: 3
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
Config/roxygen2/version: 8.0.0
Config/pak/sysreqs: nvidia-cuda-dev
Repository: https://biocstaging.r-universe.dev
Date/Publication: 2026-07-08 06:52:10 UTC
RemoteUrl: https://github.com/BiocStaging/fastPLS
RemoteRef: HEAD
RemoteSha: ef4aa0e4ea663a097fb3c10f6a4ce9f2884a278f
Packaged: 2026-07-08 08:08:42 UTC; root