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An Introduction to Copulas

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TLDR
This book discusses the fundamental properties of copulas and some of their primary applications, which include the study of dependence and measures of association, and the construction of families of bivariate distributions.
Abstract
The study of copulas and their role in statistics is a new but vigorously growing field. In this book the student or practitioner of statistics and probability will find discussions of the fundamental properties of copulas and some of their primary applications. The applications include the study of dependence and measures of association, and the construction of families of bivariate distributions. This book is suitable as a text or for self-study.

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Journal ArticleDOI

On interactive fuzzy numbers

TL;DR: A measure of interactivity between marginal distributions of a joint possibility distribution C is introduced as the expected value of the interactivity relation between the γ-level sets of its marginal distributions.
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Bivariate return periods via 2-Copulas

TL;DR: It is shown that using the 2-Copula describing the dependence features of the underlying joint distribution may greatly simplify the calculations, and even yield analytical expressions for the isolines of the return periods.
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Generalized Hoeffding-Sobol Decomposition for Dependent Variables -Application to Sensitivity Analysis

TL;DR: In this article, a generalized Hoeffding-Sobol decomposition is used to measure the sensitivity of the output with respect to the input variables, and the estimation of these new indices is discussed.
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Regression Modeling of Semicompeting Risks Data

TL;DR: A time-dependent copula model is proposed in the observable region of the data which is more flexible than standard parametric copula models for the dependence between the events and which permits estimation of the marginal distribution under weaker assumptions than in previous work on competing risks data.
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Dependence and risk spillovers between green bonds and clean energy markets

TL;DR: In this paper, the authors examined the dynamic dependence structure between green bonds and several global and sectoral clean energy (CE) markets by using several time-invariant and time-varying copula approaches over the period from 5 July 2011 to 24 February 2020.