CLX: CLX-test for two sample means

In meca7653/HDtest-2018-8: High Dimensional Hypothesis Testing for Mean Vectors, Covariance Matrices, and White Noise of Vector Time Series

Description

Testing the equality of two high dimensional mean vectors using the testing procedure by Cai, Liu and Xia (2014).

Usage

CLX(X, Y, alpha, DNAME)

Arguments

X	The n x p data matrix from the sample 1
Y	The n x p data matrix from the sample 2.
alpha	The prescribed level of significance
DNAME	Default input.

Details

Implementing testing procedure proposed by Cai, Liu, and Xia (2014) to test the equality of two sample high dimensional mean vectors under the assumption of sparsity of signals.

Value

Value of testing statistic, p-value, alternative hypothesis, and the name of testing procedure.

Author(s)

Tong He

References

T. Cai, W. Liu, and Y. Xia (2014). Two-sample test of high dimensional means under dependence. J. R. Statist. Soc. B. 76, 349–372

meca7653/HDtest-2018-8 documentation built on May 16, 2019, 3:13 p.m.