https://hal.science/hal-05352069>, and <https://hal.science/hal-05352061> highlighted fitting and cross-validating PLS-based Cox models to censored big data.">

bigPLScox: Partial Least Squares for Cox Models with Big Matrices (original) (raw)

Provides Partial least squares Regression and various regular, sparse or kernel, techniques for fitting Cox models for big data. Provides a Partial Least Squares (PLS) algorithm adapted to Cox proportional hazards models that works with 'bigmemory' matrices without loading the entire dataset in memory. Also implements a gradient-descent based solver for Cox proportional hazards models that works directly on 'bigmemory' matrices. Bertrand and Maumy (2023) <https://hal.science/hal-05352069>, and <https://hal.science/hal-05352061> highlighted fitting and cross-validating PLS-based Cox models to censored big data.

Version: 0.6.0
Depends: R (≥ 4.0.0)
Imports: bigmemory, bigalgebra, bigSurvSGD, caret, doParallel, foreach, kernlab, methods, Rcpp, risksetROC, rms, sgPLS, survAUC, survcomp, survival
LinkingTo: BH, Rcpp, RcppArmadillo, bigmemory
Suggests: bench, knitr, plsRcox, mvtnorm, readr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-11-11
DOI: 10.32614/CRAN.package.bigPLScox
Author: Frederic Bertrand ORCID iD [cre, aut], Myriam Maumy-BertrandORCID iD [aut]
Maintainer: Frederic Bertrand <frederic.bertrand at lecnam.net>
BugReports: https://github.com/fbertran/bigPLScox/issues/
License: GPL-3
URL: https://fbertran.github.io/bigPLScox/,https://github.com/fbertran/bigPLScox/
NeedsCompilation: yes
SystemRequirements: C++17
Classification/MSC: 62N01, 62N02, 62N03, 62N99
Citation: bigPLScox citation info
Materials: README, NEWS
CRAN checks: bigPLScox results [issues need fixing before 2025-11-26]

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