View source: R/covk_2001Schott.R
covk.2001Schott | R Documentation |
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.
covk.2001Schott(dlist)
dlist |
a list of length |
a (list) object of S3
class htest
containing:
a test statistic.
p
-value under H_0
.
alternative hypothesis.
name of the test.
name(s) of provided sample data.
schott_tests_2001SHT
## 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)
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