Maximum pseudo-likelihood estimation based on estimated residuals in copula semiparametric models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10436629" target="_blank" >RIV/00216208:11320/21:10436629 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=3dHfToFlHG" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=3dHfToFlHG</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/sjos.12498" target="_blank" >10.1111/sjos.12498</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Maximum pseudo-likelihood estimation based on estimated residuals in copula semiparametric models

Popis výsledku v původním jazyce

This paper deals with an estimation of the dependence structure of a multidimensional response variable in the presence of a multivariate covariate. It is assumed that the covariate affects only the marginal distributions through regression models while the dependence structure, which is described by a copula, is unaffected. A parametric estimation of the copula function is considered with focus on the maximum pseudo-likelihood method. It is proved that under some appropriate regularity assumptions the estimator calculated from the residuals has the same asymptotic distribution as the estimator based on the unobserved errors. In such case one can ignore the fact that the response is first adjusted for the effect of the covariate. The theoretical results are accompanied by a Monte Carlo simulation study which illustrates that the maximum pseudo-likelihood estimator based on residuals may behave poorly when the stated regularity assumptions are not satisfied.

Název v anglickém jazyce

Maximum pseudo-likelihood estimation based on estimated residuals in copula semiparametric models

Popis výsledku anglicky

This paper deals with an estimation of the dependence structure of a multidimensional response variable in the presence of a multivariate covariate. It is assumed that the covariate affects only the marginal distributions through regression models while the dependence structure, which is described by a copula, is unaffected. A parametric estimation of the copula function is considered with focus on the maximum pseudo-likelihood method. It is proved that under some appropriate regularity assumptions the estimator calculated from the residuals has the same asymptotic distribution as the estimator based on the unobserved errors. In such case one can ignore the fact that the response is first adjusted for the effect of the covariate. The theoretical results are accompanied by a Monte Carlo simulation study which illustrates that the maximum pseudo-likelihood estimator based on residuals may behave poorly when the stated regularity assumptions are not satisfied.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Scandinavian Journal of Statistics

ISSN

0303-6898

e-ISSN

—

Svazek periodika

48

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

41

Strana od-do

1433-1473

Kód UT WoS článku

000596688100001

EID výsledku v databázi Scopus

2-s2.0-85097200686