Fast Partial Least Squares for High-Dimensional Data R package fastPLS version 0.3 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. Software Depends: R (>= 4.6.0) Imports: methods, float Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Stefano Cacciatore <tkcaccia@gmail.com> Comprehensive R Archive Network (CRAN) 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>) MIT + file LICENSE (https://CRAN.R-project.org/package=fastPLS/LICENSE) 2026-09-28 application/tgz https://CRAN.R-project.org/package=fastPLS doi:10.32614/CRAN.package.fastPLS