Conditionalization of Copula-Based Models

Dorota Kurowicka ()
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Dorota Kurowicka: Delft Institute of Applied Mathematics, Delft University of Technology, 2628 CD Delft, The Netherlands

Decision Analysis, 2012, vol. 9, issue 3, 219-230

Abstract: Copula models are becoming increasingly popular in engineering and financial applications. They provide a flexible way of constructing joint distributions with arbitrary one-dimensional margins and a wide variety of dependence structures. This paper studies different types of conditionalization of copula-based models. We conditionalize these models in the usual way on point values but also propose a different type of conditionalization on a new margin. This new type of conditionalization is motivated by experience with a model built for application in modeling risk in civil aviation. Changing one margin in a copula model is very easy; however, it is not equivalent to conditionalizing on a new margin. For this purpose, the technique presented by Holland and Wang [Holland PW, Wang YJ (1987) Dependence function for continuous bivariate densities. Commun. Statist. Theory Methods 16(3):867--876], called marginal replacement, is used. The main result of this paper allows a simplified way of conditionalizing on more than one univariate margin in a normal copula model.

Keywords: copula; marginal replacement; local dependence function; mixed derivative measure of interaction; iterative proportional fitting; Bayesian belief nets (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ordeca:v:9:y:2012:i:3:p:219-230

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