npqcs.Q: Function to plot the Q chart

In mflores72000/qcr: Quality Control Review

Function to plot the Q chart

Description

This function is used to compute statistics required by the Non Parametric Q chart.

Usage

npqcs.Q(x, ...)

## Default S3 method:
npqcs.Q(
  x,
  G,
  data.name = NULL,
  limits = NULL,
  method = c("Tukey", "Liu", "Mahalanobis", "RP", "LD"),
  alpha = 0.01,
  plot = FALSE,
  ...
)

## S3 method for class 'npqcd'
npqcs.Q(
  x,
  data.name,
  limits = NULL,
  method = c("Tukey", "Liu", "Mahalanobis", "RP", "LD"),
  alpha = 0.01,
  plot = FALSE,
  ...
)

Arguments

x	An object of class "npqcd".
...	Arguments passed to or from methods.
G	The x as a matrix, data frame or list. If it is a matrix or data frame, then each row is viewed as one multivariate observation.
data.name	A string that specifies the title displayed on the plots. If not provided it is taken from the name of the object x.
limits	A two-value vector specifying the control limits lower and central.
method	Character string which determines the depth function used. method can be "Tukey" (the default), "Liu", "Mahalanobis", "RP" Random Project or "LD" Likelihood depth.
alpha	It is the significance level (0.01 for default)
plot	Logical value. If TRUE a Q chart should be plotted.

References

Regina Liu (1995)

Examples

## Not run:  
##
##  Continuous data 
##
library(qcr)
set.seed(12345)
mu<-c(0,0)
Sigma<- matrix(c(1,0,0,1),nrow = 2,ncol = 2)
u <- c(2,2)
S <- matrix(c(4,0,0,4),nrow = 2,ncol = 2)
G <- rmvnorm(540, mean = mu, sigma = Sigma)
x<- rmvnorm(40,mean=u,sigma = S)
x <- rbind(G[501:540,],x)
n <- 4 # samples
m <- 20  # measurements
k <- 2  # number of variables
x.a <- array(,dim=c(n,k,m))
for (i in 1:m){
x.a[,,i] <- x[(1+(i-1)*n):(i*n),] }
M <- G[1:500,]
data.npqcd <- npqcd(x.a,M)
str(data.npqcd)
res.npqcs <- npqcs.Q(data.npqcd,method = "Liu", alpha=0.025)
str(res.npqcs)
summary(res.npqcs)
plot(res.npqcs,title =" Q Control Chart")
## End(Not run)

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