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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
R2,980 Discovery Miles 29 800 Ships in 12 - 19 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
R3,354 Discovery Miles 33 540 Ships in 10 - 15 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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