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 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 [cre, aut], Myriam Maumy-Bertrand [aut] 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: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=plsRcox to link to this page.
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