mean2.1958Dempster {SHT}

Two-sample Test for High-Dimensional Means by Dempster (1958, 1960)

Description

Given two multivariate data X and Y of same dimension, it tests

H_0 : \mu_x = \mu_y\quad vs\quad H_1 : \mu_x \neq \mu_y

using the procedure by Dempster (1958, 1960).

Usage

mean2.1958Dempster(X, Y)

Arguments

X

an (n_x \times p) data matrix of 1st sample.

Y

an (n_y \times p) data matrix of 2nd sample.

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

Dempster AP (1958). “A High Dimensional Two Sample Significance Test.” The Annals of Mathematical Statistics, 29(4), 995–1010. ISSN 0003-4851.

Dempster AP (1960). “A Significance Test for the Separation of Two Highly Multivariate Small Samples.” Biometrics, 16(1), 41. ISSN 0006341X.

Examples

## CRAN-purpose small example
smallX = matrix(rnorm(10*3),ncol=3)
smallY = matrix(rnorm(10*3),ncol=3)
mean2.1958Dempster(smallX, smallY) # run the test


## empirical Type 1 error 
niter   = 1000
counter = rep(0,niter)  # record p-values
for (i in 1:niter){
  X = matrix(rnorm(50*5), ncol=10)
  Y = matrix(rnorm(50*5), ncol=10)
  
  counter[i] = ifelse(mean2.1958Dempster(X,Y)$p.value < 0.05, 1, 0)
}

## print the result
cat(paste("\n* Example for 'mean2.1958Dempster'\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=""))