CLX.test.equalcov: Cai, Liu, and Xia equal means test under equal covariances

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

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)


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