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 |
| 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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