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EMPIRICAL LIKELIHOOD BASED TESTING FOR MULTIVARIATE REGULAR VARIATION
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DOI：10.1214/24-AOS2472.png)
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Abstract
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Multivariate regular variation is a common assumption in the statistics literature and needs to be verified in real-data applications. We develop a novel hypothesis test for multivariate regular variation, employing localized empirical likelihood. We establish the weak convergence of the test statistic to a nonstandard, distribution-free limit and hence can provide universal critical values for the test. We show the very good finite-sample behavior of the procedure through simulations and apply the test to several real-data examples.
Keywords:
phrases. Asymptotic theory
distribution-free
empirical likelihood
empirical process
multvariate tail
regular variation
tail index
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3.7
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2.8K
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2.9W
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