cov2.2012LC | R Documentation |
Given two multivariate data X and Y of same dimension, it tests
H_0 : Σ_x = Σ_y\quad vs\quad H_1 : Σ_x \neq Σ_y
using the procedure by Li and Chen (2012).
cov2.2012LC(X, Y, use.unbiased = TRUE)
X |
an (n_x \times p) data matrix of 1st sample. |
Y |
an (n_y \times p) data matrix of 2nd sample. |
use.unbiased |
a logical; |
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.
li_two_2012SHT
## CRAN-purpose small example smallX = matrix(rnorm(10*4),ncol=5) smallY = matrix(rnorm(10*4),ncol=5) cov2.2012LC(smallX, smallY) # run the test ## Not run: ## empirical Type 1 error : use 'biased' version for faster computation niter = 1000 counter = rep(0,niter) for (i in 1:niter){ X = matrix(rnorm(500*25), ncol=10) Y = matrix(rnorm(500*25), ncol=10) counter[i] = ifelse(cov2.2012LC(X,Y,use.unbiased=FALSE)$p.value < 0.05,1,0) print(paste0("iteration ",i,"/1000 complete..")) } ## print the result cat(paste("\n* Example for 'cov2.2012LC'\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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