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.
- Version0.6.0
- R version≥ 4.0.0
- LicenseGPL-3
- Needs compilation?Yes
- bigPLScox citation info
- Last release11/11/2025
Documentation
Team
Frederic Bertrand
MaintainerShow author detailsMyriam Maumy-Bertrand
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