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```
#' Beta Control Charts
#'
#' The Beta Chart presents the control limits based on the Beta probability distribution. It was can be used for monitoring fraction data from Binomial distribution as replacement of the p-Charts. The Beta Chart was applied for monitoring the variables in three real studies, and it was compared to the control limits with three schemes. The comparative analysis showed that: (i) Beta approximation to the Binomial distribution was more appropriate with values confined in the [0, 1]- interval; and (ii) the charts proposed were more sensitive to the average run length (ARL), in both in-control and out-of-control processes monitoring. The Beta Charts outperform the Shewhart control charts analyzed for monitoring fraction data.This package was made based on the qcc package. See \link[qcc]{qcc}.
#' @aliases bcc
#' @description Create an object of class \code{'qcc'} to perform statistical quality control. This object may then be used to plot Beta Control Charts.
#' @export bcc
#' @import qcc
#' @import methods
#' @import stats
#' @param data a data frame, a matrix or a vector containing observed data for the variable to chart. Each row of a data frame or a matrix, and each value of a vector, refers to a sample or ''rationale group''.
#' @param type a character string specifying the group statistics to compute. There are two possible types: \code{1} for discrete data and \code{2} for continuous data.
#' @param center a value specifying the center of group statistics or the ''target'' value of the process.
#' @param sizes a value or a vector of values specifying the sample sizes associated with each group. If data is continuous this parameter should be ignored
#' @param std.dev a value or an available method specifying the within-group standard deviation(s) of the process.
#' @param limits a two-values vector specifying control limits.
#' @param data.name a string specifying the name of the variable which appears on the plots. If not provided is taken from the object given as data.
#' @param labels a character vector of labels for each group.
#' @param newdata a data frame, matrix or vector, as for the \code{data} argument, providing further data to plot but not included in the computations.
#' @param newsizes a vector as for the \code{sizes} argument providing further data sizes to plot but not included in the computations.
#' @param newdata.name a string specifying the name of the variable which appears on the plots. If not provided is taken from the object given as newdata.
#' @param newlabels a character vector of labels for each new group defined in the argument \code{newdata}.
#' @param nsigmas a numeric value specifying the number of sigmas to use for computing control limits. It is ignored when the \code{confidence.level} argument is provided.
#' @param confidence.level a numeric value between 0 and 1 specifying the confidence level of the computed probability limits.
#' @param rules a value or a vector of values specifying the rules to apply to the chart. See \link[qcc]{shewhart.rules} for possible values and their meaning.
#' @param plot logical. If \code{TRUE} a Shewhart chart is plotted.
#' @param ... further arguments are ignored.
#' @return Returns an object of class \code{'qcc'}.
#'
#'
#' @references SANT'ANNA, Ângelo M. O; CATEN, Carla Schwengber ten. Beta control charts forsave monitoring fraction data. Expert Systems With Applications, p. 10236-10243. 1 set. 2012.
#' @references Scrucca, L. (2004). qcc: an R package for quality control charting and statistical process control. \emph{R News} 4/1, 11-17.
#'
#'
#'@examples
#'data("Drapper1998data")
#'bcc(data = Drapper1998data, type = "2")
#'data("Montgomery2005")
#'bcc(data=Montgomery2005$Defective, sizes = Montgomery2005$Sample, type=1)
#'
#'
bcc<-function(data, type = c("1", "2"),
sizes, center, std.dev, limits, data.name, labels, newdata, newsizes,
newdata.name, newlabels, nsigmas = 3, confidence.level=0.9, rules = shewhart.rules,
plot = TRUE, ...){
if (type == 1){
qcc(data = data, type = "beta",
sizes = sizes, center = center, std.dev = std.dev, limits = limits, data.name = data.name, labels = labels, newdata = newdata, newsizes = newsizes,
newdata.name = newdata.name, newlabels = newlabels, nsigmas = 3, confidence.level = confidence.level, rules = shewhart.rules,
plot = TRUE, ...)
}
if (type == 2){
qcc(data = data, type = "beta.p",
center = center, std.dev = std.dev, limits = limits, data.name = data.name, labels = labels, newdata = newdata, newsizes = newsizes,
newdata.name = newdata.name, newlabels = newlabels, nsigmas = 3, confidence.level = confidence.level, rules = shewhart.rules,
plot = TRUE, ...)
}
}
```

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