Nonparametric testing for no covariate effects in conditional copulas

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10365648" target="_blank" >RIV/00216208:11320/17:10365648 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1080/02331888.2016.1258070" target="_blank" >http://dx.doi.org/10.1080/02331888.2016.1258070</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/02331888.2016.1258070" target="_blank" >10.1080/02331888.2016.1258070</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Nonparametric testing for no covariate effects in conditional copulas

Popis výsledku v původním jazyce

In dependence modelling using conditional copulas, one often imposes the working assumption that the covariate influences the conditional copula solely through the marginal distributions. This so-called (pairwise) simplifying assumption is almost standardly made in vine copula constructions. However, in recent literature evidence was provided that such an assumption might not be justified. Among the first issues is thus to test for its appropriateness. In this paper nonparametric tests for the null hypothesis of the simplifying assumption are proposed, and their asymptotic behaviours, under the null hypothesis and under some local alternatives, are established. The tests are fully nonparametric in nature: not requiring choices of copula families nor knowledge of the marginals. In a simulation study, the finite-sample size and power performances of the tests are investigated, and compared with these of the few available tests. A real data application illustrates the use of the tests.

Název v anglickém jazyce

Nonparametric testing for no covariate effects in conditional copulas

Popis výsledku anglicky

In dependence modelling using conditional copulas, one often imposes the working assumption that the covariate influences the conditional copula solely through the marginal distributions. This so-called (pairwise) simplifying assumption is almost standardly made in vine copula constructions. However, in recent literature evidence was provided that such an assumption might not be justified. Among the first issues is thus to test for its appropriateness. In this paper nonparametric tests for the null hypothesis of the simplifying assumption are proposed, and their asymptotic behaviours, under the null hypothesis and under some local alternatives, are established. The tests are fully nonparametric in nature: not requiring choices of copula families nor knowledge of the marginals. In a simulation study, the finite-sample size and power performances of the tests are investigated, and compared with these of the few available tests. A real data application illustrates the use of the tests.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GJ15-04774Y" target="_blank" >GJ15-04774Y: Modelování závislosti veličin pomocí kopulí za přítomnosti kovariát</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Statistics

ISSN

0233-1888

e-ISSN

—

Svazek periodika

51

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

35

Strana od-do

475-509

Kód UT WoS článku

000399481400001

EID výsledku v databázi Scopus

2-s2.0-84997270947