R/auxiliary_functions.R

In diagL1: Routines for Fit, Inference and Diagnostics in Linear L1 and LAD Models

#main author: Kévin Allan Sales Rodrigues

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#Funções auxiliares para quantreg

#' Function to calculate robust lambda estimator
#'
#' Function to compute a robust lambda estimator, which is based on the residuals order statistics.
#'
#' @param model A linear model L1 fitted with the \code{rq} function from the \code{quantreg} package.
#' @returns Robust lambda estimator, which is based on the residuals order statistics.
#' @export
#'
#' @examples
#' data(stackloss)
#' model_L1 = regL1(stack.loss ~ stack.x)
#' lambda_ros(model_L1)
#'
lambda_ros = function(model){
  return(model$lambda_ros)
}

#' Function to estimate lambda via MLE
#'
#'
#' @param model A linear model L1 fitted with the \code{rq} function from the \code{quantreg} package.
#' @returns lambda MLE (Maximum Likelihood Estimator) estimator.
#' @export
#'
#' @examples
#' data(stackloss)
#' model_L1 = regL1(stack.loss ~ stack.x)
#' lambda_mle(model_L1)
#'
lambda_mle = function(model){
  return(model$MAE)
}


#' Function to calculate SAE
#'
#' Function to calculate SAE (Sum of Absolute Errors) of the adjusted model.
#'
#' @param model A linear model L1 fitted with the \code{rq} function from the \code{quantreg} package.
#' @returns SAE (Sum of Absolute Errors).
#' @export
#'
#' @examples
#' data(stackloss)
#' model_L1 = regL1(stack.loss ~ stack.x)
#' SAE(model_L1)
#'
SAE = function(model){
 return(model$SAE)
}