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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:
1
Seitenangaben Beitrag:
1-21
Sprache:
en
Volltext / DOI:
doi:10.1515/demo-2022-0100
Verlag / Institution:
Walter de Gruyter GmbH
E-ISSN:
2300-2298
Publikationsdatum:
01.01.2022
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