bigPLScox
Partial Least Squares for Cox Models with Big Matrices
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.8.1 |
rolling source/ R- | bigPLScox_0.8.1.tar.gz |
709.1 KiB |
0.8.1 |
rolling linux/jammy R-4.5 | bigPLScox_0.8.1.tar.gz |
709.1 KiB |
0.8.1 |
latest source/ R- | bigPLScox_0.8.1.tar.gz |
709.1 KiB |
0.8.1 |
2026-04-23 source/ R- | bigPLScox_0.8.1.tar.gz |
709.1 KiB |