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Elements of Copula Modeling with R

Part of the Use R! Book Series

DOI: 10.1007/978-3-319-89635-9

ISBN: 978-3-319-89634-2

Publisher: Springer International Publishing - Springer Journals

Jan 10, 2019

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Chapter 1Introduction

Hofert, Marius; Kojadinovic, Ivan; Mächler, Martin; Yan, Jun

Pages: 1 –8

[Assume that one is given the two bivariate data sets displayed in Fig. 1.1 and asked to compare them in terms of the “dependence” between the two underlying variables. The first (respectively, second) data set, denoted by (xi1, xi2), i ∈{1, …, n} (respectively, (yi1, yi2), i ∈{1, …, n}), is...
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Chapter 2Copulas

Hofert, Marius; Kojadinovic, Ivan; Mächler, Martin; Yan, Jun

Pages: 9 –79

[This chapter offers a basic introduction to copulas and presents their main properties along with the most important theoretical results such as the Fréchet-Hoeffding bounds, Sklar’s Theorem, and the invariance principle.]
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Chapter 3Classes and Families

Hofert, Marius; Kojadinovic, Ivan; Mächler, Martin; Yan, Jun

Pages: 81 –132

[This chapter introduces the main copula classes and the corresponding sampling procedures, along with some copula transformations that are important for practical purposes.]
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Chapter 4Estimation

Hofert, Marius; Kojadinovic, Ivan; Mächler, Martin; Yan, Jun

Pages: 133 –165

[This chapter addresses the estimation of copulas from a parametric, semi-parametric, and nonparametric perspective.]
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Chapter 5Graphical Diagnostics, Tests, and Model Selection

Hofert, Marius; Kojadinovic, Ivan; Mächler, Martin; Yan, Jun

Pages: 167 –196

[This chapter presents graphical diagnostics and statistical tests, and discusses model selection for copulas.]
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Chapter 6Ties, Time Series, and Regression

Hofert, Marius; Kojadinovic, Ivan; Mächler, Martin; Yan, Jun

Pages: 197 –254

[This chapter is concerned with more advanced topics in copula modeling such as the handling of ties, time series, and covariates (in a regression-like setting).]

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