Dependence Modeling with Copulas (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

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9781466583221: Dependence Modeling with Copulas (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
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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 of copulas, dependence measures, and statistical tools makes this book a valuable reference for researchers and experienced practitioners. I expect the statistical approach to the field will be especially appealing for the JASA audience." -Journal of the American Statistical Association, December 2015 "Harry Joe's impressive new book Dependence Modeling with Copulas will undoubtedly become a key reference work in the field. ... this excellent book will be a welcome addition to the library of anyone with an interest in copulas, multivariate statistics, or models of dependence. The researcher will find the book indispensable while the applied statistician will find much of value to guide the choice of copula models in data analysis. The book is packed with information ... an interested reader will return to the text again and again, making new discoveries each time." -Journal of Time Series Analysis, 2015

Reseña del editor:

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.

The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models.

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Harry Joe
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Descripción Chapman and Hall/CRC, 2014. Condición: New. book. Nº de ref. del artículo: M1466583223

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Descripción Taylor Francis Inc, United States, 2016. Hardback. Condición: New. Language: English . Brand New Book. 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. The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models. Nº de ref. del artículo: AAS9781466583221

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Descripción Chapman and Hall/CRC, 2016. HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: IQ-9781466583221

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Descripción Taylor Francis Inc, United States, 2016. Hardback. Condición: New. Language: English . Brand New Book. 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. The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models. Nº de ref. del artículo: AAS9781466583221

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Descripción Taylor Francis Inc, United States, 2016. Hardback. Condición: New. Language: English . This book usually ship within 10-15 business days and we will endeavor to dispatch orders quicker than this where possible. Brand New Book. 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. The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models. Nº de ref. del artículo: BTE9781466583221

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Descripción Taylor and Francis 2016-09-21, Boca Raton |London, 2016. hardback. Condición: New. Nº de ref. del artículo: 9781466583221

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Descripción CRC Press. Hardcover. Condición: New. 480 pages. Dimensions: 10.1in. x 7.0in. x 1.1in.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. The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Hardcover. Nº de ref. del artículo: 9781466583221

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Descripción Chapman & Hall, 2014. Hardcover. Condición: Brand New. 462 pages. 9.00x6.00x1.00 inches. In Stock. Nº de ref. del artículo: z-1466583223

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