View source: R/mvar2_2012ZXC.R
| mvar2.2012ZXC | R Documentation | 
Given two univariate samples x and y, it tests
H_0 : \mu_x = \mu_y, \sigma_x^2 = \sigma_y^2 \quad vs \quad H_1 : \textrm{ not } H_0
using exact null distribution for likelihood ratio statistic.
mvar2.2012ZXC(x, y)
| x | a length- | 
| y | a 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.
zhang_exact_2012SHT
## CRAN-purpose small example
x = rnorm(10)
y = rnorm(10)
mvar2.2012ZXC(x, y)
## Not run: 
## empirical Type 1 error 
niter   = 1000
counter = rep(0,niter)  # record p-values
for (i in 1:niter){
  x = rnorm(100)  # sample x from N(0,1)
  y = rnorm(100)  # sample y from N(0,1)
  
  counter[i] = ifelse(mvar2.2012ZXC(x,y)$p.value < 0.05, 1, 0)
  print(paste("* mvar2.2012ZXC : iteration ",i,"/",niter," complete.",sep=""))
}
## print the result
cat(paste("\n* Example for 'mvar2.2012ZXC'\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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