R/outliers.R

In outForest: Multivariate Outlier Detection and Replacement

#' Extracts Outliers
#'
#' Extracts outliers from object of class 'outForest'. The outliers are sorted by their absolute score in descending fashion.
#'
#' @param object An object of class 'outForest'.
#' @param ... Arguments passed from or to other methods.
#' @return A \code{data.frame} with one row per outlier. The columns are as follows:
#' \itemize{
#'   \item \code{row}, \code{col}: Row and column in original data with outlier.
#'   \item \code{observed}: Observed value.
#'   \item \code{predicted}: Predicted value.
#'   \item \code{rmse}: Scaling factor used to normalize the difference between observed and predicted.
#'   \item \code{score}: Outlier score defined as (observed-predicted)/rmse.
#'   \item \code{threshold}: Threshold above which an outlier score counts as outlier.
#'   \item \code{replacement}: Value used to replace observed value.
#' }
#' @export
#' @examples
#' x <- outForest(iris)
#' outliers(x)
outliers <- function(object, ...) {
  UseMethod("outliers")
}

#' @describeIn outliers Default method not implemented yet.
#' @export
outliers.default <- function(object, ...) {
  stop("No default method available yet.")
}

#' @describeIn outliers Extract outliers from outForest object.
#' @export
outliers.outForest <- function(object, ...) {
  object$outliers
}