Usage
getIndic(lp,lpnew,Surv.rsp,Surv.rsp.new,times.auc=seq(10,1000,10),
times.prederr=1:500,train.fit,train.fit.cph,tmax.train=365,
tmax.test=365,TR,TE,plot.it=TRUE)
getIndicCV(lp,lpnew,Surv.rsp,Surv.rsp.new,times.auc=seq(10,1000,10),
times.prederr=1:500,train.fit,plot.it=FALSE,
tmax.train=max(Surv.rsp[,"time"][ object$Surv.rsp[,"status"] == 1 ]),
tmax.test=max(Surv.rsp.new[,"time"][ object$Surv.rsp.new[,"status"] == 1 ]))
getIndicCViAUCSH(lp,lpnew,Surv.rsp,Surv.rsp.new,times.auc=seq(10,1000,10),
times.prederr=1:500,train.fit,plot.it=FALSE,
tmax.train=max(Surv.rsp[,"time"][ object$Surv.rsp[,"status"] == 1 ]),
tmax.test=max(Surv.rsp.new[,"time"][ object$Surv.rsp.new[,"status"] == 1 ]))
getIndicCViAUCSurvROCTest(lp,lpnew,Surv.rsp,Surv.rsp.new,times.auc=seq(10,1000,10),
times.prederr=1:500,train.fit,plot.it=FALSE,
tmax.train=max(Surv.rsp[,"time"][ object$Surv.rsp[,"status"] == 1 ]),
tmax.test=max(Surv.rsp.new[,"time"][ object$Surv.rsp.new[,"status"] == 1 ]))
correctp.cox(x, y, eta, K, kappa, select, fit, verbose=FALSE)
spls.cox(x, y, K, eta, kappa = 0.5, select = "pls2",
fit = "regression", scale.x = TRUE, scale.y = FALSE, eps = 1e-04,
maxstep = 100, trace = FALSE)
ust(b, eta)
spls.dv(Z, eta, kappa, eps, maxstep)
pls.cox(X, Y, ncomp = 2, mode = c("regression", "canonical",
"invariant", "classic"), max.iter = 500, tol = 1e-06, scale.X=TRUE, scale.Y=TRUE, ...)
predict.pls.cox(object, newdata, scale.X=TRUE, scale.Y=TRUE,...)