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Dokumenttyp:
Zeitschriftenaufsatz 
Autor(en):
Tepegjozova, Marija; Zhou, Jing; Claeskens, Gerda; Czado, Claudia 
Titel:
Nonparametric C- and D-vine-based quantile regression 
Abstract:
Quantile regression is a field with steadily growing importance in statistical modeling. It is a complementary method to linear regression, since computing a range of conditional quantile functions provides more accurate modeling of the stochastic relationship among variables, especially in the tails. We introduce a nonrestrictive and highly flexible nonparametric quantile regression approach based on C- and D-vine copulas. Vine copulas allow for separate modeling of marginal distributions and t...    »
 
Stichworte:
vine copulas; conditional quantile function; nonparametric pair-copulas 
Dewey Dezimalklassifikation:
510 Mathematik 
Zeitschriftentitel:
Dependence Modeling 
Jahr:
2022 
Band / Volume:
10 
Jahr / Monat:
2022-02 
Quartal:
1. Quartal 
Monat:
Feb 
Heft / Issue:
Seitenangaben Beitrag:
1-21 
Sprache:
en 
Volltext / DOI:
Verlag / Institution:
Walter de Gruyter GmbH 
E-ISSN:
2300-2298 
Publikationsdatum:
01.01.2022