Cai, Liu, and Xia equal means test under equal covariances

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Description

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 can be assumed equal.

Usage

1

Arguments

X

the n by p data matrix for sample one.

Y

the m by p data matrix for sample two.

Value

TSvalue

the value of the test statistic.

pvalue

the two-sided p-value for the test statistic.

Author(s)

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

References

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

See Also

CLX.sim.equalcov

Examples

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## 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.equalcov(X,Y)
	
	
## End(Not run)