DEPENDENCE MODELING: VINE COPULA HANDBK

“This book gives a clear and authoritative exposition of the vine methodology, which has recently emerged as a flexible tool for modeling high-dimensional data through pair-copula constructions. Leaders in the field join forces to provide a broad and insightful account of the existing theory as well as many new results of practical interest, from the enumeration and generation of regular vines to copula modeling and estimation using C-vines and D-vines. Many instructive illustrations and state-of-the-art applications are also presented, in static and dynamic contexts. Short of being ‘D-vine’, this important volume ought to become a classic of the copula literature and a useful reference for developers and practitioners alike!”

“Dependence modeling beyond linear correlation has become a key theme of research, with considerable promise in numerous applications. Especially the field of hierarchical model building has gained a lot of interest in this context. The notion of vine combines graphic with analytic tools from the realm of copulas, and offers a computationally as well as structurally interesting environment for the construction of multivariate models. Written by experts in the field, this handbook will be a most useful addition to a fast growing field of research in probability and statistics.”

“In this well-written and comprehensive book, an international team of more than one dozen researchers presents a thorough introduction to dependence modeling using vine copulas. The book assembles material formerly only available in journal articles and conference proceedings in a coherent and very readable manner. In 17 chapters, the authors present the basic and advanced vine copula properties and techniques for researchers wishing to employ this methodology in practice. The book has numerous examples, illustrations, algorithms, references, and directions for future work, and promises to be an important reference for years to come.”