New Asymptotic Results for Bernstein Estimators for Conditional Copulas

Noël Veraverbeke ()
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Noël Veraverbeke: University of Hasselt

Chapter Chapter 22 in Asymptotic and Methodological Statistics, 2026, pp 431-444 from Springer

Abstract: Abstract Conditional copulas are very essential in the modeling of dependence in multivariate data in the presence of a random covariate. Several authors studied the asymptotics for the conditional empirical copula function. Bernstein polynomials provide an interesting tool for obtaining smooth versions of these non-parametric estimators. Here we provide new asymptotic results for Bernstein-based versions of estimators for a conditional copula, its first order partial derivatives and its density function. As an application we deal with the estimation of a risk ratio for bivariate data in the presence of covariate.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-032-07178-1_22

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DOI: 10.1007/978-3-032-07178-1_22

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