R/cv.plsRglmmodel.default.R

In plsRglm: Partial Least Squares Regression for Generalized Linear Models

#' @rdname cv.plsRglm
#' @export
cv.plsRglmmodel.default <- function(object,dataX,nt=2,limQ2set=.0975,modele="pls", family=NULL, K=5, NK=1, grouplist=NULL, random=TRUE, scaleX=TRUE, scaleY=NULL, keepcoeffs=FALSE, keepfolds=FALSE, keepdataY=TRUE, keepMclassed=FALSE, tol_Xi=10^(-12), weights, method, verbose=TRUE,...)
  {
  mf0 <- match.call(expand.dots = FALSE)
m0 <- match(c("object","dataX","nt","limQ2set","modele", "family", "K", "NK", "grouplist", "random", "scaleX", "scaleY", "keepcoeffs", "keepfolds", "keepdataY", "keepMclassed", "tol_Xi", "weights", "method", "verbose"), names(mf0), 0L)
mf0$dataY <- mf0$object
m <- match(c("dataY","dataX","nt","limQ2set","modele", "family", "K", "NK", "grouplist", "random", "scaleX", "scaleY", "keepcoeffs", "keepfolds", "keepdataY", "keepMclassed", "tol_Xi", "weights", "method", "verbose"), names(mf0), 0L)
mf <- mf0[c(1L, m)]
mf[[1L]] <- as.name("PLS_glm_kfoldcv")
cvmodel <- eval(mf, parent.frame())

callf0 <- match.call()
callf0$dataY <- mf0$object
call0 <- c(toString(callf0[[1]]),names(callf0))
call1 <- call0[!(call0=="") & !(call0=="object")]
cvmodel$call <- callf0[call1]
cvmodel$call[[1L]] <- as.name(toString(callf0[[1]]))

  class(cvmodel) <- "cv.plsRglmmodel"
  return(cvmodel)
}