Abstract
The problem of multiple hypothesis testing with correlated test statistics is a very important problem in statistical literature. Specifically, we consider the case when the joint distribution of the test statistics is a multivariate normal distribution with an unknown mean vector and compound symmetric correlation structure. Our goal is to identify nonzero entries of the mean vector. Bogdan et al. (2011) solved this problem when test statistics are independent normals along with the study of asymptotic optimality in a Bayesian decision theoretic sense. The case under dependence was left as a challenging open problem. The solution is intuitive and permutation invariant, does not assume sparsity unlike Bogdan et al. (2011) and is validated through simulation studies.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
