CLX.test.unequalcov: Cai, Liu, and Xia equal means test under unequal covariances
In highD2pop: Two-Sample Tests for Equality of Means in High Dimension

Description Usage Arguments Value Author(s) References See Also Examples

Performs the test in Cai, Liu, and Xia (2014) for the equality of two p by 1 population mean vectors given samples of sizes n and m when the popoulation covariance matrices are assumed to be unequal.

1	CLX.test.unequalcov(X, Y)

`X`	the `n` by `p` data matrix for sample one.
`Y`	the `m` by `p` data matrix for sample two.

`TSvalue`	the value of the test statistic.
`pvalue`	the two-sided p-value for the test statistic.

Karl Gregory kgregory@mail.uni-mannheim.de, http://www.stat.tamu.edu/~kbgregory.

Cai, T. T., Liu, W. & Xia, Y. (2014). Two-sample test of high dimensional means under dependence. J. R. Statist. Soc. B.

CLX.sim.equalcov

## Not run: 
	
data(chr1qseg)
	
	impute <- function(x) 	
	{ 	
		x[which(is.na(x))] <- mean(x,na.rm=TRUE)
		return(x)
	}
	
	X <- apply(chr1qseg$X,2,impute)
	Y <- apply(chr1qseg$Y,2,impute)
	
	CLX.test.unequalcov(X,Y)
	

## End(Not run)