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Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications (Hardcover): Matthias Scherer, Jan-Frederik Mai Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications (Hardcover)
Matthias Scherer, Jan-Frederik Mai
R2,796 Discovery Miles 27 960 Ships in 18 - 22 working days

This book provides the reader with a 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 advanced undergraduate or graduate students with a firm background in stochastics. Alongside the theoretical foundation, ready-to-implement algorithms and many examples make this book a valuable tool for anyone who is applying the methodology.

Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications (Hardcover, Second Edition): Jan-Frederik Mai,... Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications (Hardcover, Second Edition)
Jan-Frederik Mai, Matthias Scherer
R3,095 Discovery Miles 30 950 Ships in 18 - 22 working days

'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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