qcs.one: Function to plot the Shewhart xbar.one chart

In mflores72000/qcr: Quality Control Review

Function to plot the Shewhart xbar.one chart

Description

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

Usage

qcs.one(x, ...)

## Default S3 method:
qcs.one(
  x,
  var.index = 1,
  sample.index = 2,
  covar.index = NULL,
  covar.names = NULL,
  data.name = NULL,
  sizes = NULL,
  center = NULL,
  std.dev = c("MR", "SD"),
  k = 2,
  conf.nsigma = 3,
  limits = NULL,
  plot = FALSE,
  ...
)

## S3 method for class 'qcd'
qcs.one(
  x,
  center = NULL,
  std.dev = c("MR", "SD"),
  k = 2,
  conf.nsigma = 3,
  limits = NULL,
  plot = FALSE,
  ...
)

Arguments

x	An object of class "qcd".
...	Arguments passed to or from methods.
var.index	A scalar with the column number corresponding to 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 to the index fo each group (sample).
covar.index	Optional. A scalar or numeric vector with the column number(s) corresponding to the covariate(s). Alternativelly it can be a character vector with the names of the covariates.
covar.names	Optional. A string or vector of strings indicating the 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, it is taken from the object given as data.
sizes	Optional. A value or a vector of values specifying the sample sizes associated with each group. For continuous data the sample sizes are obtained counting the non-NA elements of the sample.index vector. For attribute variable the argument sizes is required.
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 in case of a continuous process variable.
k	Number of successive pairs of observations for computing the standard deviation based on moving ranges of k points.
conf.nsigma	A numeric value used to compute control limits, specifying the number of standard deviations (if conf.nsigma > 1) or the confidence level (if 0 < conf.nsigma < 1).
limits	A two-value vector specifying control limits.
plot	Logical value. If TRUE a xbar.one chart should be plotted.

Examples

##
##  Continuous data 
##
library(qcr)
x <- c(33.75, 33.05, 34, 33.81, 33.46, 34.02, 33.68, 33.27, 33.49, 33.20,
      33.62, 33.00, 33.54, 33.12, 33.84)

sample <- 1:length(x)
datos <- data.frame(x,sample)
datos.qcd <- qcd(datos)

res.qcs <- qcs.one(datos.qcd)
class(res.qcs)
summary(res.qcs)  
 plot(res.qcs, title = "Control Chart Xbar.one for pistonrings")  

mflores72000/qcr documentation built on July 1, 2023, 9:17 p.m.