View source: R/mvar2_2012ZXC.R
mvar2.2012ZXC | R Documentation |
Given two univariate samples x and y, it tests
H_0 : μ_x = μ_y, σ_x^2 = σ_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-n data vector. |
y |
a length-m data vector. |
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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