Journal
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
Volume 80, Issue 8, Pages 873-887Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00949650902822564
Keywords
generalized p-value; generalized variable test; Johansen test; moment approximation; modified Nel-Van der Merwe test; Type I error
Ask authors/readers for more resources
In this article, we consider the problem of comparing several multivariate normal mean vectors when the covariance matrices are unknown and arbitrary positive definite matrices. We propose a parametric bootstrap (PB) approach and develop an approximation to the distribution of the PB pivotal quantity for comparing two mean vectors. This approximate test is shown to be the same as the invariant test given in [Krishnamoorthy and Yu, Modified Nel and Van der Merwe test for the multivariate Behrens-Fisher problem, Stat. Probab. Lett. 66 (2004), pp. 161-169] for the multivariate Behrens-Fisher problem. Furthermore, we compare the PB test with two existing invariant tests via Monte Carlo simulation. Our simulation studies show that the PB test controls Type I error rates very satisfactorily, whereas other tests are liberal especially when the number of means to be compared is moderate and/or sample sizes are small. The tests are illustrated using an example.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available