% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cchart.p.R
\name{cchart.p}
\alias{cchart.p}
\title{p-chart}
\usage{
cchart.p(x1 = NULL, n1 = NULL, type = "norm", p1 = NULL, x2 = NULL,
  n2 = NULL, phat = NULL, p2 = NULL)
}
\arguments{
\item{x1}{The phase I data that will be plotted (if it is a phase I chart).}

\item{n1}{A value or a vector of values specifying the sample sizes
associated with each group for the phase I data.}

\item{type}{The type of p-chart to be plotted. The options are "norm"
(traditional Shewhart p-chart), "CF" (Cornish Fisher p-chart) and "std"
(standardized p-chart). If not specified, a Shewhart p-chart will be
plotted.}

\item{p1}{The data used to estimate the phat (x1 / n1).}

\item{x2}{The phase II data that will be plotted in a phase II chart.}

\item{n2}{A value or a vector of values specifying the sample sizes
associated with each group for the phase II data.}

\item{phat}{The estimate of p.}

\item{p2}{The values corresponding to x2 / n2.}
}
\value{
Return a p-chart.
}
\description{
This function builds p-charts.
}
\details{
For a phase I p-chart, n1 must be specified and either x1 or p1.  For a
phase II p-chart, n2 must be specified, plus x2 or p2 and either phat, x1
and n1, or p1 and n1.  The Shewhart is based on normal-aprroximation and
should be used only for large values of np or n*p (n*p > 6).
}
\examples{

data(binomdata)
attach(binomdata)
cchart.p(x1 = Di[1:12], n1 = ni[1:12])
cchart.p(x1 = Di[1:12], n1 = ni[1:12], type = "CF", x2 = Di[13:25], n2 = ni[13:25])
cchart.p(type = "std", p2 = Di[13:25], n2 = ni[13:25], phat = 0.1115833)

}
\references{
Montgomery, D.C.,(2008)."Introduction to Statistical Quality
Control". Chapter 11. Wiley
}
\author{
Daniela R. Recchia, Emanuel P. Barbosa
}