plsRcox: Partial Least Squares Regression for Cox Models and Related Techniques (original) (raw)
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.
Version: | 1.7.7 |
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Depends: | R (≥ 2.4.0) |
Imports: | survival, plsRglm, lars, pls, kernlab, mixOmics, risksetROC, survcomp, survAUC, rms |
Suggests: | survivalROC, plsdof |
Published: | 2022-11-29 |
DOI: | 10.32614/CRAN.package.plsRcox |
Author: | Frederic Bertrand |
Maintainer: | Frederic Bertrand <frederic.bertrand at utt.fr> |
BugReports: | https://github.com/fbertran/plsRcox/issues/ |
License: | GPL-3 |
URL: | http://fbertran.github.io/plsRcox/,https://github.com/fbertran/plsRcox/ |
NeedsCompilation: | no |
Classification/MSC: | 62N01, 62N02, 62N03, 62N99 |
Citation: | plsRcox citation info |
Materials: | README |
In views: | Survival |
CRAN checks: | plsRcox results |
Documentation:
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