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person:"Gassebner, Martin"
~person:"Einmahl, John H. J."
~subject:"Nonparametric statistics"
~subject:"Wahrscheinlichkeitsrechnung"
~type_genre:"Graue Literatur"
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Nonparametric statistics
Wahrscheinlichkeitsrechnung
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Statistical distribution
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Statistische Verteilung
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tail dependence
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extreme value statistics
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functional limit theorems
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non-identical distributions
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stable tail dependence function
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Gassebner, Martin
Einmahl, John H. J.
Chen Zhou
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Daouia, Abdelaati
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Schaumburg, Julia
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Discussion paper / Center for Economic Research, Tilburg University
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ECONIS (ZBW)
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Tail copula estimation for heteroscedastic extremes
Einmahl, John H. J.
;
Chen Zhou
-
2024
Persistent link: https://www.econbiz.de/10014467520
Saved in:
2
Extreme value inference for general heterogeneous data
He, Yi
;
Einmahl, John H. J.
-
2024
Persistent link: https://www.econbiz.de/10014528470
Saved in:
3
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
Saved in:
4
Testing the multivariate regular variation model
Einmahl, John H. J.
;
Yang, Fan
;
Chen Zhou
-
2018
Persistent link: https://www.econbiz.de/10011920524
Saved in:
5
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
Saved in:
6
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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