qcr (version 0.1-18)

qcs.cusum: Function to plot cusum chart

Description

This function is used to compute statistics required by the cusum chart.

Usage

qcs.cusum(x, ...)
"qcs.cusum"(x, var.index = 1, sample.index = 2, covar.index = NULL, covar.names = NULL, data.name = NULL, sizes = NULL, center = NULL, std.dev = NULL, decision.interval = 5, se.shift = 1, plot = FALSE, ...)
"qcs.cusum"(x, center = NULL, std.dev = NULL, decision.interval = 5, se.shift = 1, plot = FALSE, ...)

Arguments

x

an R object (used to select the method). See details.

...

arguments passed to or from methods.

sizes

a value or a vector of values specifying the sample sizes associated with each group.

center

a value specifying the center of group statistics or the ''target'' value of the process.

std.dev

a value or an available method specifying the within-group standard deviation(s) of the process. Several methods are available for estimating the standard deviation.

decision.interval

A numeric value specifying the number of standard errors of the summary statistics at which the cumulative sum is out of control.

se.shift

The amount of shift to detect in the process, measured in standard errors of the summary statistics.

plot

a logical value indicating should be plotted.

var.index

a scalar with the column number corresponding the observed data for the variable (the variable quality). Alternativelly can be a string with the name of the quality variable.

sample.index

a scalar with the column number corresponding the index each group (sample).

covar.index

optional. A scalar or numeric vector with the column number(s) corresponding to the covariate(s). Alternativelly can be a character vector with the names of the covariates.

covar.names

optional. A string or vector of strings with names for the covariate columns. Only valid if there is more than one column of data. By default, takes the names from the original object.

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.

Examples

library(qcr)
data(pistonrings)
attach(pistonrings)
res.qcd <- qcd(pistonrings, type.data = "dependence")
res.qcs <- qcs.cusum(res.qcd, type = "cusum")
summary(res.qcs)
plot(res.qcs)