plsRcox: Partial Least Squares Regression for Cox Models and Related Techniques

Provides Partial least squares Regression and various regular, sparse or kernel, techniques for fitting Cox models in high dimensional settings <doi:10.1093/bioinformatics/btu660>, Bastien, P., Bertrand, F., Meyer N., Maumy-Bertrand, M. (2015), Deviance residuals-based sparse PLS and sparse kernel PLS regression for censored data, Bioinformatics, 31(3):397-404. Cross validation criteria were studied in <arXiv:1810.02962>, Bertrand, F., Bastien, Ph. and Maumy-Bertrand, M. (2018), Cross validating extensions of kernel, sparse or regular partial least squares regression models to censored data.

Package details

AuthorFrederic Bertrand [cre, aut] (<>), Myriam Maumy-Bertrand [aut] (<>)
MaintainerFrederic Bertrand <>
Package repositoryView on CRAN
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plsRcox documentation built on Dec. 1, 2022, 1:31 a.m.