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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "bigPLSR" in publications use:'
type: software
license: GPL-3.0-only
title: 'bigPLSR: Partial Least Squares Regression Models with Big Matrices'
version: 0.7.2
identifiers:
- type: doi
  value: 10.32614/CRAN.package.bigPLSR
abstract: 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) <https://doi.org/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) <https://doi.org/10.1016/j.csda.2007.01.004>, Rosipal
  (2004) <https://doi.org/10.1007/978-3-540-45167-9_17>, Rosipal (2019) <https://ieeexplore.ieee.org/document/8616346>,
  Song, Wang, and Bai (2024) <https://doi.org/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.
authors:
- family-names: Bertrand
  given-names: Frederic
  email: frederic.bertrand@lecnam.net
  orcid: https://orcid.org/0000-0002-0837-8281
- family-names: Maumy
  given-names: Myriam
  email: myriam.maumy@ehesp.fr
  orcid: https://orcid.org/0000-0002-4615-1512
preferred-citation:
  type: manual
  title: Partial Least Squares Regression Models with Big Matrices
  authors:
  - family-names: Bertrand
    given-names: Frederic
    email: frederic.bertrand@lecnam.net
    orcid: https://orcid.org/0000-0002-0837-8281
  - family-names: Maumy
    given-names: Myriam
    email: myriam.maumy@ehesp.fr
    orcid: https://orcid.org/0000-0002-4615-1512
  publisher:
    name: manual
  year: '2025'
  notes: R package version 0.7.2
  url: https://fbertran.github.io/bigPLSR/
repository: https://fbertran.r-universe.dev
repository-code: https://github.com/fbertran/bigPLSR
commit: 2033eb023bea3771b67270a4f81fe3d922b587de
url: https://fbertran.github.io/bigPLSR/
date-released: '2025-11-26'
contact:
- family-names: Bertrand
  given-names: Frederic
  email: frederic.bertrand@lecnam.net
  orcid: https://orcid.org/0000-0002-0837-8281
references:
- type: generic
  title: PLS models and their extension for big data
  authors:
  - family-names: Maumy
    given-names: Myriam
  - family-names: Bertrand
    given-names: Frédéric
  year: '2023'
  medium: Conference presentation at the Joint Statistical Meetings (JSM 2023)
  location:
    name: Toronto, Ontario, Canada
  notes: Aug 5–10, 2023
- type: generic
  title: 'bigPLS: Fitting and cross-validating PLS-based Cox models to censored big
    data'
  authors:
  - family-names: Maumy
    given-names: Myriam
  - family-names: Bertrand
    given-names: Frédéric
  year: '2023'
  medium: 'Conference presentation at BioC2023: The Bioconductor Annual Conference'
  location:
    name: Dana-Farber Cancer Institute, Boston, MA, USA
  notes: Aug 2–4, 2023
  doi: 10.7490/f1000research.1119546.1
  url: https://doi.org/10.7490/f1000research.1119546.1