#' @method print qrsvm
#' @export
print.qrsvm <- function(x, ...) {
cat(paste0("Quantile Regression SVM. Cost is ", x$cost), fill = TRUE)
cat(paste0("Estimated Quantile is ", x$tau), fill = TRUE)
}
#' @method summary qrsvm
#' @export
summary.qrsvm <- function(object, ...) {
idx <- c(4L:6L, 8L:12L)
mapply(function(n, x){
cat(paste(n, " is ", x), fill = TRUE)
}, names(object[idx]), object[idx])
invisible(NULL)
}
#' Fitted values of class "qrsvm"
#'
#' @param object An object of class \link{qrsvm}.
#' @param ... other arguments.
#' @return A numeric vector of fitted values.
#' @method fitted qrsvm
#' @importFrom stats fitted
#' @export
fitted.qrsvm <- function(object, ...) {
return(object$fitted)
}
#' Predict an Object of class "qrsvm"
#'
#' @param object An object of class \link{qrsvm}.
#' @param newdata The predictors of the predictable data in an n X m Matrix.
#' @param ... other arguments.
#' @return A numeric vector of predicted values.
#' @method predict qrsvm
#' @importFrom stats predict
#' @importFrom kernlab kernelMult
#' @export
predict.qrsvm <- function(object, newdata, ...) {
if (!is.matrix(newdata))
newdata <- as.matrix(newdata)
xold <- object$xtrain
if (ncol(newdata) != ncol(xold))
stop("Newdata has different number of columns than xtrain please check consistency!")
return(kernelMult(object$kernel, newdata, xold, object$alpha) + object$b0)
}
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