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Document type:
Zeitungsartikel 
Author(s):
Killiches, M., Kraus, D. and Czado, C. 
Title:
Model distances for vine copulas in high dimensions 
Abstract:
Vine copulas are a flexible class of dependence models consisting of bivariate building blocks and have proven to be particularly useful in high dimensions. Classical model distance measures require multivariate integration and thus suffer from the curse of dimensionality. In this paper, we provide numerically tractable methods to measure the distance between two vine copulas even in high dimensions. For this purpose, we consecutively develop three new distance measures based on the Kullback–Lei...    »
 
Keywords:
Vine copulas, Model distances, Kullback–Leibler, Jeffreys distance, Monte Carlo integration 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Statistics and Computing 
Year:
2018 
Journal volume:
28 
Year / month:
2018-03 
Quarter:
1. Quartal 
Month:
Mar 
Journal issue:
Pages contribution:
323–341 
Language:
en 
WWW:
Publisher:
Springer 
Status:
Erstveröffentlichung 
Date of publication:
11.02.2017 
TUM Institution:
Lehrstuhl für Mathematische Statistik 
Format:
Text