R/plsRcox-package.R
plsRcox-package-hash-at-import-boot.RdProvides 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.
#> Warning: data set ‘Cornell’ not foundcv.modpls<-cv.plsR(Y~.,data=Cornell,nt=6,K=6)#> Error in cv.plsR(Y ~ ., data = Cornell, nt = 6, K = 6): impossible de trouver la fonction "cv.plsR"#> Error in cvtable(summary(cv.modpls)): impossible de trouver la fonction "cvtable"