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Spatial dependence and space-time trends in extreme event
Einmahl, John H. J.; Ferreira, Ana; Haan, Laurens de; … - 2020
Persistent link: https://www.econbiz.de/10012182625
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Estimation of extreme depth-based quantile regions
He, Yi; Einmahl, John H. J. - 2014
Persistent link: https://www.econbiz.de/10011282830
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Testing the multivariate regular variation model
Einmahl, John H. J.; Yang, Fan; Chen Zhou - 2018
Persistent link: https://www.econbiz.de/10011920524
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Ultimate 100m world records through extreme-value theory
Einmahl, John H. J.; Smeets, Sander G. W. R. - 2009
Persistent link: https://www.econbiz.de/10003865811
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Estimating extreme bivariate quantile regions
Einmahl, John H. J.; Haan, Laurens de - 2009
Persistent link: https://www.econbiz.de/10003863842
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Unified extreme value estimation for heterogeneous data
Einmahl, John H. J.; He, Yi - 2020
Persistent link: https://www.econbiz.de/10012291907
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Extreme value inference for general heterogeneous data
He, Yi; Einmahl, John H. J. - 2024
Persistent link: https://www.econbiz.de/10014528470
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Estimation of the marginal expected shortfall : the mean when a related variable is extreme
Cai, Juan-Juan; Einmahl, John H. J.; Haan, Laurens de; … - 2012
Persistent link: https://www.econbiz.de/10009630355
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Bridging Centrality and Extremity : Refining Empirical Data Depth using Extreme Value Statistics
Einmahl, John H. J.; Li, Jun; Liu, Regina Y. - 2015
Persistent link: https://www.econbiz.de/10011350125
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Asymptotically distribution-free goodness-of-fit testing for tail copulas
Can, Sami Umut; Einmahl, John H. J.; Khmaladze, Estate V.; … - 2014
Persistent link: https://www.econbiz.de/10011283328