R/reconstructGBMdata.R

In DexGroves/gbm-lrd: Generalized Boosted Regression Models

reconstructGBMdata <- function(x)
{
   if(class(x) != "gbm")
   {
      stop( "This function is for use only with objects having class 'gbm'" )
   } else
   if (is.null(x$data))
   {
      stop("Cannot reconstruct data from gbm object. gbm() was called with keep.data=FALSE")
   } else
   if (x$distribution$name=="multinomial")
   {
      y <- matrix(x$data$y, ncol=x$num.classes, byrow=FALSE)
      yn <- apply(y, 1, function(z,nc) {(1:nc)[z == 1]},
                  nc = x$num.classes)
      y <- factor(yn, labels=x$classes)
      xdat <- matrix(x$data$x, ncol=ncol(x$data$x.order), byrow=FALSE)
      d <- data.frame(y, xdat)
      names(d) <- c(x$response.name, x$var.names)
   } else
   if (x$distribution$name == "coxph")
   {
      xdat <- matrix(x$data$x, ncol=ncol(x$data$x.order), byrow=FALSE)
      status <- x$data$Misc
      y <- x$data$y[order(x$data$i.timeorder)]
      d <- data.frame(y, status, xdat)
      names(d) <- c(x$response.name[-1], colnames(x$data$x.order))
   }
   else
   {
      y <- x$data$y
      xdat <- matrix(x$data$x, ncol=ncol(x$data$x.order), byrow=FALSE)
      d <- data.frame(y, xdat)
      rn <- ifelse(length(x$response.name) > 1, x$response.name[2], x$response.name)
      names(d) <- c(rn, colnames(x$data$x.order))
   }
   invisible(d)
}