pamr.train <-

function (data, n.threshold = 30, offset.percent = 50, remove.zeros = TRUE) 

{

  this.call <- match.call()

  if (!is.null(data$y)) {

    problem.type <- "class"

  }

  y <- as.factor(data$y)

  ytest <- NULL

  xtest <- NULL

  prior <- table(y)/length(y)

  junk <- nsc(data$x, y = y, offset.percent = offset.percent, n.threshold = n.threshold, prior = prior,

              remove.zeros = remove.zeros)

  junk$call <- this.call

  junk$problem.type <- problem.type

  class(junk) = "pamrtrained"

  junk

}