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Dokumenttyp:
Zeitungsartikel 
Autor(en):
Nagler, T. and Czado, C. 
Titel:
Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas 
Abstract:
Practical applications of nonparametric density estimators in more than three dimensions suffer a great deal from the well-known curse of dimensionality: convergence slows down as dimension increases. We show that one can evade the curse of dimensionality by assuming a simplified vine copula model for the dependence between variables. We formulate a general nonparametric estimator for such a model and show under high-level assumptions that the speed of convergence is independent of dimension. We...    »
 
Stichworte:
Asymptotic; Classification; Copula; Dependence; Kernel density; Vine 
Dewey Dezimalklassifikation:
510 Mathematik 
Zeitschriftentitel:
Journal of Multivariate Analysis 
Jahr:
2016 
Band / Volume:
151 
Jahr / Monat:
2016-10 
Quartal:
4. Quartal 
Monat:
Oct 
Heft / Issue:
Seitenangaben Beitrag:
69-89 
Reviewed:
ja 
Sprache:
en 
Verlag / Institution:
Academic Press, Inc. 
Verlagsort:
Orlando, FL, USA 
Status:
Verlagsversion / published 
TUM Einrichtung:
Lehrstuhl für Mathematische Statistik 
Format:
Text 
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