cchart.p {IQCC} | R Documentation |
p-chart
Description
This function builds p-charts.
Usage
cchart.p(x1 = NULL, n1 = NULL, type = "norm", p1 = NULL, x2 = NULL,
n2 = NULL, phat = NULL, p2 = NULL)
Arguments
x1 |
The phase I data that will be plotted (if it is a phase I chart). |
n1 |
A value or a vector of values specifying the sample sizes associated with each group for the phase I data. |
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. |
p1 |
The data used to estimate the phat (x1 / n1). |
x2 |
The phase II data that will be plotted in a phase II chart. |
n2 |
A value or a vector of values specifying the sample sizes associated with each group for the phase II data. |
phat |
The estimate of p. |
p2 |
The values corresponding to x2 / n2. |
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).
Value
Return a p-chart.
Author(s)
Daniela R. Recchia, Emanuel P. Barbosa
References
Montgomery, D.C.,(2008)."Introduction to Statistical Quality Control". Chapter 11. Wiley
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)