R/chi.probability.R

In Katrinebch/ExamST516:

#' @export
#' @title Chi square probability
#' @usage chi.probability(x, df, n)
#' @keywords bootstrap
#' @description This function applies the Monte Carlo method to generate a chi-squared distribution.
#' @param x the point where we want to calculate the probability.
#' @param df degree of freedom
#' @param n number of random numbers for each variable.
#' @author Katrine Eriksen and Katrine Bach \cr
#' Department of mathematics and computer science (IMADA) \cr
#' University of Southern Denmark \cr
#' \email{kater13@student.sdu.dk} and \email{kabac13@student.sdu.dk}
#' @examples chi.probability(10,4,100)


chi.probability <-function(x, df, n){
  #WARNING/STOPS
  if (!is.numeric(x)){stop("x must be numeric")}
  if (x<1){warning("Generates wrong chi-probability")}
  
  if(df==0){stop("The degrees of freedom must be greater than zero")}
  if (df<0){stop("The degrees of freedom must be positive")}
  if (!is.numeric(df)){stop("The degrees of freedom must be numeric")}
  
  if(n==0){warning("n must be positive")}
  if (n<0){stop("Impossible to generate a amount of variables")}
  if (!is.numeric(n)){stop("n must be numeric")}
  
  
  set.seed(13)
  summ <- 0
  Y <- 0
  for (i in 1:df) {
    Y <- rnorm(n, mean=0, sd=1)
    Yianden <- Y^2
    summ <- summ + Yianden
  }
  blup <- ecdf(summ)
  plot(blup)
  p <-1-blup(x)
  return(p)

}