Function to plot the Q chart

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

Usage

npqcs.Q(x, ...)

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

# S3 method for 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

if (FALSE) { 
##
##  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")}