bigPLSR

Fast partial least squares (PLS) for dense and out-of-core data. Provides SIMPLS (straightforward implementation of a statistically inspired modification of the PLS method) and NIPALS (non-linear iterative partial least-squares) solvers, plus kernel-style PLS variants ('kernelpls' and 'widekernelpls') with parity to 'pls'. Optimized for 'bigmemory'-backed matrices with streamed cross-products and chunked BLAS (Basic Linear Algebra Subprograms) (XtX/XtY and XXt/YX), optional file-backed score sinks, and deterministic testing helpers. Includes an auto-selection strategy that chooses between XtX SIMPLS, XXt (wide) SIMPLS, and NIPALS based on (n, p) and a configurable memory budget. About the package, Bertrand and Maumy (2023) https://hal.science/hal-05352069, and https://hal.science/hal-05352061 highlighted fitting and cross-validating PLS regression models to big data. For more details about some of the techniques featured in the package, Dayal and MacGregor (1997) doi:10.1002/(SICI)1099-128X(199701)11:1%3C73::AID-CEM435%3E3.0.CO;2-%23, Rosipal & Trejo (2001) https://www.jmlr.org/papers/v2/rosipal01a.html, Tenenhaus, Viennet, and Saporta (2007) doi:10.1016/j.csda.2007.01.004, Rosipal (2004) doi:10.1007/978-3-540-45167-9_17, Rosipal (2019) https://ieeexplore.ieee.org/document/8616346, Song, Wang, and Bai (2024) doi:10.1016/j.chemolab.2024.105238. Includes kernel logistic PLS with 'C++'-accelerated alternating iteratively reweighted least squares (IRLS) updates, streamed reproducing kernel Hilbert space (RKHS) solvers with reusable centering statistics, and bootstrap diagnostics with graphical summaries for coefficients, scores, and cross-validation workflows, alongside dedicated plotting utilities for individuals, variables, ellipses, and biplots. The streaming backend uses far less memory and keeps memory bounded across data sizes. For PLS1, streaming is often fast enough while preserving a small memory footprint; for PLS2 it remains competitive with a bounded footprint. On small problems that fit comfortably in RAM (random-access memory), dense in-memory solvers are slightly faster; the crossover occurs as n or p grow and the Gram/cross-product cost dominates.

Documentation signals are not tracked yet for this package.

1Stars

0Forks

0Open issues

0Open PRs

0Releases

41Commits

1Contributors

4 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/fbertran/bigplsr on 2026-07-19.

Nothing depends on this yet.

1 release. R releases are shown for context.

First published

2025-12-01

Total releases

1 / 1 yrs

License

GPL-3 OSI

Download size

2.0 MB

Installed size

not tracked yet

With dependencies

not tracked yet