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Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications
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Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications

Second Edition

Book Details

Format Hardback or Cased Book
ISBN-10 9813149248
ISBN-13 9789813149243
Edition Second Edition
Publisher World Scientific Publishing Co Pte Ltd
Imprint World Scientific Publishing Co Pte Ltd
Country of Manufacture GB
Country of Publication GB
Publication Date Aug 2nd, 2017
Print length 356 Pages
Weight 646 grams
Dimensions 16.10 x 23.60 x 2.40 cms
Product Classification: Stochastics
Ksh 20,700.00
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The book provides the background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for graduate and advanced undergraduate students with a firm background in stochastics. Besides the theoretical foundation, ready-to-implement algorithms and many examples make the book a valuable tool for anyone who is applying the methodology.

'The book remains a valuable tool both for statisticians who are already familiar with the theory of copulas and just need to develop sampling algorithms, and for practitioners who want to learn copulas and implement the simulation techniques needed to exploit the potential of copulas in applications.'Mathematical ReviewsThe book provides the background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for graduate and advanced undergraduate students with a firm background in stochastics. Besides the theoretical foundation, ready-to-implement algorithms and many examples make the book a valuable tool for anyone who is applying the methodology.

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