University of Cincinnati Lindner College of Business

Robust Hypothesis Testing via Lq-Likelihood
Yichen Qin

Status: Published
Year: 2017
Publication Name: Statistica Sinica
Volume: 27, Page Number(s): 1793-1813


This article introduces a robust hypothesis testing procedure: the Lq-likelihood-ratio-type test (LqRT). By deriving the asymptotic distribution of this test statistic, the authors demonstrate its robustness both analytically and numerically, and they investigate the properties of both its influence function and its breakdown point. A proposed method to select the tuning parameter q offers a good efficiency/robustness trade-off, compared with the traditional likelihood ratio test (LRT) and other robust tests. A simulation and real data analysis provides further evidence of the advantages of the proposed LqRT method. In particular, for the special case of testing the location parameter in the presence of gross error contamination, the LqRT dominates the Wilcoxon-Mann-Whitney test and the sign test at various levels of contamination.

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UC Authors

Yichen Qin
Yichen Qin