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Document type:
Masterarbeit 
Author(s):
Alexej Brauer 
Title:
Kernel Estimation of Conditional Copula Densities 
Abstract:
In many cases, the dependence structure between random variables varies according to the values of measured covariates. A natural approach studying these type of models is the usage of conditional copulas. Here we provide an introduction to this concept and propose a novel fully nonparametric method for the estimation of conditional copula densities. Our procedure is based on transformation kernels combined with local linear regression. The asymptotic properties are studied and a bandwidth selec...    »
 
Keywords:
Asymptotic, conditional, copula, density, kernel, nonparametric 
Advisor:
Claudia Czado, Thomas Nagler 
Year:
2016 
Quarter:
4. Quartal 
Year / month:
2016-12 
Month:
Dec 
Language:
en 
University:
Technische Universität München 
Faculty:
Fakultät für Mathematik 
TUM Institution:
Lehrstuhl für Mathematische Statistik