covk.2001Schott {SHT}

Test for Homogeneity of Covariances by Schott (2001)

Description

Given univariate samples X_1~,\ldots,~X_k, it tests

H_0 : \Sigma_1 = \cdots \Sigma_k\quad vs\quad H_1 : \textrm{at least one equality does not hold}

using the procedure by Schott (2001) using Wald statistics. In the original paper, it provides 4 different test statistics for general elliptical distribution cases. However, we only deliver the first one with an assumption of multivariate normal population.

Usage

covk.2001Schott(dlist)

Arguments

dlist

a list of length k where each element is a sample matrix of same dimension.

Value

a (list) object of S3 class htest containing:

statistic

a test statistic.

p.value

p-value under H_0.

alternative

alternative hypothesis.

method

name of the test.

data.name

name(s) of provided sample data.

References

Schott JR (2001). “Some tests for the equality of covariance matrices.” Journal of Statistical Planning and Inference, 94(1), 25–36. ISSN 03783758.

Examples

## CRAN-purpose small example
tinylist = list()
for (i in 1:3){ # consider 3-sample case
  tinylist[[i]] = matrix(rnorm(10*3),ncol=3)
}
covk.2001Schott(tinylist) # run the test

## Not run: 
## test when k=5 samples with (n,p) = (100,20)
## empirical Type 1 error 
niter   = 1000
counter = rep(0,niter)  # record p-values
for (i in 1:niter){
  mylist = list()
  for (j in 1:5){
     mylist[[j]] = matrix(rnorm(100*20),ncol=20)
  }
  
  counter[i] = ifelse(covk.2001Schott(mylist)$p.value < 0.05, 1, 0)
}

## print the result
cat(paste("\n* Example for 'covk.2001Schott'\n","*\n",
"* number of rejections   : ", sum(counter),"\n",
"* total number of trials : ", niter,"\n",
"* empirical Type 1 error : ",round(sum(counter/niter),5),"\n",sep=""))

## End(Not run)