R/coefs.plsRglm.raw.R

In plsRglm: Partial Least Squares Regression for Generalized Linear Models

#' Raw coefficients for bootstrap computations of PLSGLR models
#' 
#' A function passed to \code{boot} to perform bootstrap.
#' 
#' 
#' @param dataset dataset to resample
#' @param ind indices for resampling
#' @param nt number of components to use
#' @param modele type of modele to use, see \link{plsRglm}
#' @param family glm family to use, see \link{plsRglm}
#' @param maxcoefvalues maximum values allowed for the estimates of the
#' coefficients to discard those coming from singular bootstrap samples
#' @param ifbootfail value to return if the estimation fails on a bootstrap
#' sample
#' @param verbose should info messages be displayed ?
#' @return estimates on a bootstrap sample or \code{ifbootfail} value if the
#' bootstrap computation fails.
#' @author Frédéric Bertrand\cr
#' \email{frederic.bertrand@@utt.fr}\cr
#' \url{https://fbertran.github.io/homepage/}
#' @seealso See also \code{\link{bootplsglm}}.
#' @keywords models
#' @examples
#' 
#' data(Cornell)
#' 
#' # (Y,X) bootstrap of a PLSGLR model
#' set.seed(250)
#' modplsglm <- coefs.plsRglm.raw(Cornell[,-8],1:nrow(Cornell),nt=3,
#' modele="pls-glm-family",family=gaussian,maxcoefvalues=1e5,
#' ifbootfail=rep(0,3),verbose=FALSE)
#' 
#' @export coefs.plsRglm.raw
coefs.plsRglm.raw <-
  function(dataset,
           ind,
           nt,
           modele,
           family = NULL,
           maxcoefvalues,
           ifbootfail,
           verbose)
  {
    tempcoefs <-
      try(PLS_glm_wvc(
        dataY = dataset[ind, 1],
        dataX = dataset[ind,-1],
        nt = nt,
        modele = modele,
        family = family,
        keepcoeffs = TRUE,
        verbose = verbose
      )$coeffs,
      silent = TRUE)
    Cond <- FALSE
    try(Cond <-
          is.numeric(tempcoefs) & all(abs(tempcoefs) < maxcoefvalues),
        silent = TRUE)
    if (Cond) {
      return(tempcoefs)
    } else {
      return(ifbootfail)
    }
  }