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Dependence modeling with copulas

Author: Harry Joe
Publisher: Boca Raton : CRC Press, [2015] ©2015
Series: Monographs on statistics and applied probability (Series), 134.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas. It also  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Joe, Harry.
Dependence modelling with copulas.
Boca Raton : CRC Press, Taylor & Francis Group, [2015]
(DLC) 2014018932
(OCoLC)880349851
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Harry Joe
ISBN: 9781466583238 1466583231 9781322635651 132263565X 1466583223 9781466583221
OCLC Number: 884594998
Notes: "A Chapman & Hall book."
Description: 1 online resource (xviii, 462 pages) : illustrations, tables.
Contents: A Chapter 1. Introduction --
Chapter 2. Basics: dependence, tail behavior and asymmetries --
Chapter 3. Copula construction methods --
Chapter 4. Parametric copula families and properties --
Chapter 5. Inference, diagnostics and model selection --
Chapter 6. Computing and algorithms --
Chapter 7. Applications and data examples --
Chapter 8. Theorems for properties of copulas --
Appendix A. Laplace transforms and Archimedean generators.
Series Title: Monographs on statistics and applied probability (Series), 134.
Responsibility: Harry Joe.

Abstract:

Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas. It also discusses other multivariate constructions and parametric copula families that have different tail properties and presents extensive material on dependence and tail properties to assist in copula model selection.

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"... a 'must have' for someone seriously involved in dependence modeling with copulas, especially with a focus on modeling real data. The huge collection of facts and references for certain families Read more...

 
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