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Abstract
Assuming that all components of a normal mean vector are simultaneously non negative or non positive, we consider a multivariate two-sided test for testing whether the normal mean vector is equal to zero or not. Since the likelihood ratio test is accompanied with theoretical and computational complications, we discuss two kinds of approximations of the likelihood ratio test. One is based on a conservative critical value determined by a certain inequality. The other is constructed by the approximation of the likelihood ratio test proposed by Tang et al. (1989). We compare the likelihood ratio test and two kinds of approximations through numerical examples regarding critical values and the power of the test.
Acknowledgments
The author is deeply grateful to the referee for the helpful advice and comments for revising the article. Special thanks are due to the editors and associate editors for their constructive comments and suggestions.