mean2.mxPBF: Two-sample Mean Test with Maximum Pairwise Bayes Factor

In SHT: Statistical Hypothesis Testing Toolbox

Two-sample Mean Test with Maximum Pairwise Bayes Factor

Description

Not Written Here - No Reference Yet.

Usage

mean2.mxPBF(X, Y, a0 = 0, b0 = 0, gamma = 1, nthreads = 1)

Arguments

X	an (n_x \times p) data matrix of 1st sample.
Y	an (n_y \times p) data matrix of 2nd sample.
a0	shape parameter for inverse-gamma prior (default: 0).
b0	scale parameter for inverse-gamma prior (default: 0).
gamma	non-negative variance scaling parameter (default: 1).
nthreads	number of threads for parallel execution via OpenMP (default: 1).

Value

a (list) object of S3 class htest containing:

statistic

maximum of pairwise Bayes factor.

alternative

alternative hypothesis.

method

name of the test.

data.name

name(s) of provided sample data.

log.BF.vec

vector of pairwise Bayes factors in natural log.

Examples

## Not run: 
## empirical Type 1 error with BF threshold = 10
niter   = 1000
counter = rep(0,niter)  # record p-values
for (i in 1:niter){
  X = matrix(rnorm(100*10), ncol=10)
  Y = matrix(rnorm(200*10), ncol=10)
  
  counter[i] = ifelse(mean2.mxPBF(X,Y)$statistic > 10, 1, 0)
}

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

SHT documentation built on Nov. 3, 2022, 9:06 a.m.