Nonparametric testing for no covariate effects in conditional copulas
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Nonparametric testing for no covariate effects in conditional copulas
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GJ15-04774Y" target="_blank" >GJ15-04774Y: Using copulas for modelling dependency structure of variables in the presence of covariates</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Statistics
ISSN
0233-1888
e-ISSN
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Volume of the periodical
51
Issue of the periodical within the volume
3
Country of publishing house
DE - GERMANY
Number of pages
35
Pages from-to
475-509
UT code for WoS article
000399481400001
EID of the result in the Scopus database
2-s2.0-84997270947