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 doi:10.48550/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.
- Version1.7.7
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- plsRcox citation info
- Last release11/29/2022
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Team
Frederic Bertrand
Myriam Maumy-Bertrand
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- Imports8 packages
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