cchart.R.R
``````#' R control chart
#'
#' This function builds a R control chart.
#'
#' The Shewhart R chart was designed for phase I (at this moment).  The limits
#' of the exact R chart are the alpha/2 and 1-alpha/2 quantiles of the R
#' distribution that are calculated as estimated process sd times the quantiles
#' of the relative range (W=R/sigma) distribution.
#'
#' @aliases cchart.R
#' @param x The data to be plotted.
#' @param n The sample size.
#' @param type The type of R chart to be plotted. The options are "norm"
#' (traditional Shewhart R chart) and "tukey" (exact R chart). If not
#' specified, a Shewhart R chart will be plotted.
#' @param y The data used in phase I to estimate the standard deviation.
#' @return Return a R control chart.
#' @export
#' @author Daniela R. Recchia, Emanuel P. Barbosa
#' @import qcc
#' @examples
#'
#' data(pistonrings)
#' attach(pistonrings)
#' cchart.R(pistonrings[1:25,], 5)
#' cchart.R(pistonrings[26:40, ], 5, type = "tukey", pistonrings[1:25, ])
#'
cchart.R <- function(x, n, type = "norm", y = NULL)
{
if(type == "norm")
{
qcc(x, type = "R", xlab = "")
resu <- alpha.risk(n)
result <- signif(resu, 3)
mtext(paste("Warning: Prob. of false alarm alpha = ", result," is inflated (>> 0.0027) since the normal approximation for R is not appropriated; in order to have alpha = 0.0027 the exact distribution for R must be used."), side = 1, font = 2)
}
if(type == "tukey")
{
qcc(x, type = "R", limits = c(qtukey(0.00135, n, Inf) * sd.R(y), qtukey(0.99865, n, Inf) * sd.R(y)))
}
}``````