Package: fastPLS
Type: Package
Title: Fast Partial Least Squares for High-Dimensional Data
Version: 0.3
Date: 2026-09-26
Authors@R: c(
    person(
        "Stefano", "Cacciatore", role = c("aut", "cre"),
        email = "tkcaccia@gmail.com",
        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")
    )
    )
Description: Fast implementations of partial least squares models for
        high-dimensional regression and classification. The 'fastPLS'
        software provides compiled implementations of PLS-SVD, a
        SIMPLS-family estimator, 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. Compact latent prediction and memory-aware
        numerical routes support analyses with large predictor or
        multivariate-response matrices.
License: MIT + file LICENSE
URL: https://github.com/tkcaccia/fastPLS
BugReports: https://github.com/tkcaccia/fastPLS/issues
biocViews: Software, DimensionReduction, Classification, Regression,
        GenePrediction, GeneExpression, Metabolomics, SingleCell, GPU
SystemRequirements: Optional OpenBLAS development libraries for faster
        CPU matrix operations; optional NVIDIA CUDA Toolkit with CUDA
        Runtime, cuBLAS, cuSOLVER and cuRAND plus a compatible
        separately managed NVIDIA driver; optional Apple Metal
        framework on macOS. CPU-only builds do not require GPU
        software.
Depends: R (>= 4.6.0)
Imports: methods, float
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Config/testthat/edition: 3
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
Config/roxygen2/version: 8.1.0
Config/pak/sysreqs: nvidia-cuda-dev
Repository: https://tkcaccia.r-universe.dev
Date/Publication: 2026-09-29 09:04:02 UTC
RemoteUrl: https://github.com/tkcaccia/fastpls
RemoteRef: HEAD
RemoteSha: 17424f9228dac6c87a3f6e2b93a752a7609c016a
Packaged: 2026-09-29 16:14:07 UTC; root
Author: Stefano Cacciatore [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-7052-7156>),
  Dupe Ojo [aut] (ORCID: <https://orcid.org/0000-0002-5301-8592>),
  Leonardo Tenori [aut] (ORCID: <https://orcid.org/0000-0001-6438-059X>),
  Alessia Vignoli [aut] (ORCID: <https://orcid.org/0000-0003-4038-6596>)
Maintainer: Stefano Cacciatore <tkcaccia@gmail.com>