@techreport{261583f5c57148c68cea945ba6542026,
title = "Empirical Likelihood Based Testing for Multivariate Regular Variation",
abstract = "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 non-standard, 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 = "asymptotic theory, distribution-free, empirical likelihood, empirical process, multivariate tail, regular variation, tail index",
author = "John Einmahl and Andrea Krajina",
note = "CentER Discussion Paper Nr. 2023-001",
year = "2023",
month = jan,
day = "9",
language = "English",
volume = "2023-001",
series = "CentER Discussion Paper",
publisher = "CentER, Center for Economic Research",
type = "WorkingPaper",
institution = "CentER, Center for Economic Research",
}