ESTIMATION OF COPULA AND ITS APPLICATION ON DOUBLE DECREMENT MODELS - Nurhazanah (NIM : 201 05 020), Elis
Abstract: This thesis introduces the concept of copulas, a tool for understanding non linear dependence among multivariate outcomes. A copula is a function that links univariate marginals to their full multivariate distribution. The literature on the statistical properties and applications of copulas has been developing rapidly in recent years. This article explores some of these practical applications, focus on estimation non linear dependence of double decrement models. In addition, we describe basic properties of copulas, measures of dependence, and several families of copulas that have appeared in the literature. Then we expose a guide to identify the Archimedean copula that suited to double decrement data. Using a suitable copula,the dependence measure is quantified as Kendall=0.975. This result can be used to define the premium tariff for double decrement benefit.