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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
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Two-sample testing for tail copulas with an application to equity indices
Can, Sami Umut; Einmahl, John H. J.; Laeven, Roger J. A. - In: Journal of business & economic statistics : JBES ; a … 42 (2024) 1, pp. 147-159
Persistent link: https://www.econbiz.de/10014449844
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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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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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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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Empirical tail copulas for functional data
Einmahl, John H. J.; Segers, Johan - 2020
Persistent link: https://www.econbiz.de/10012161555
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Improved estimation of the extreme value index using related variables
Ahmed, Hanan; Einmahl, John H. J. - 2018
Persistent link: https://www.econbiz.de/10011879741
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Statistics of heteroscedastic extremes
Einmahl, John H. J.; Haan, Laurens de; Chen Zhou - 2014
Persistent link: https://www.econbiz.de/10010395089
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An M-estimator of spatial tail dependence
Einmahl, John H. J.; Kiriliouk, Anna; Krajina, Andrea; … - 2014
Persistent link: https://www.econbiz.de/10010395535
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An M-estimator for tail dependence in arbitrary dimensions
Einmahl, John H. J.; Krajina, Andrea; Segers, Johan - 2011
Persistent link: https://www.econbiz.de/10008841187