| 期刊全稱 | Analyzing Dependent Data with Vine Copulas | | 期刊簡(jiǎn)稱 | A Practical Guide Wi | | 影響因子2023 | Claudia Czado | | 視頻video | http://file.papertrans.cn/157/156814/156814.mp4 | | 發(fā)行地址 | Offers a step-by-step introduction to vine copula based dependence modeling, including model selection and estimation methods for vine copulas.Features easy-to-follow derivations and illustrations to | | 學(xué)科分類 | Lecture Notes in Statistics | | 圖書(shū)封面 |  | | 影響因子 | .This textbook provides a step-by-step introduction to the class of vine copulas, their statistical inference and applications. It focuses on statistical estimation and selection methods for vine copulas in data applications. These flexible copula models can successfully accommodate any form of tail dependence and are vital to many applications in finance, insurance, hydrology, marketing, engineering, chemistry, aviation, climatology and health..The book explains the pair-copula construction principles underlying these statistical models and discusses how to perform model selection and inference. It also derives simulation algorithms and presents real-world examples to illustrate the methodological concepts. The book includes numerous exercises that facilitate and deepen readers’ understanding, and demonstrates how the R package VineCopula can be used to explore and build statistical dependence models from scratch. In closing, the book provides insights into recent developments and open research questions in vine copula based modeling..The book is intended for students as well as statisticians, data analysts and any other quantitatively oriented researchers who are new to the field | | Pindex | Textbook 2019 |
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