Improved kernel estimation of copulas: weak convergence and goodness-of-fit testing

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F09%3A00206954" target="_blank" >RIV/00216208:11320/09:00206954 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Improved kernel estimation of copulas: weak convergence and goodness-of-fit testing

Original language description

We suggest modification of existing kernel estimators for a copula function in order to prevent corner bias problems when the second derivatives of the copula functions are unbounded. The theoretical contribution of the paper is a weak convergence resultfor the suggest estimators under conditions that are met for most copula families. We also discuss the choice of bandwidth parameters, theoretically and practically, and illustrate the finite-sample behaviour of the estimators in a simulation study. Theestimators are also applied to goodness-of-fit testing for copulas.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BA - General mathematics

OECD FORD branch

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Project

<a href="/en/project/LC06024" target="_blank" >LC06024: Jaroslav Hájek Center for Theoretical and Applied Statistics</a><br>

Continuities

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

Publication year

2009

Confidentiality

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

Name of the periodical

Annals of Statistics

ISSN

0090-5364

e-ISSN

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Volume of the periodical

37

Issue of the periodical within the volume

5B

Country of publishing house

US - UNITED STATES

Number of pages

36

Pages from-to

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UT code for WoS article

000268605000015

EID of the result in the Scopus database

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