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Analyzing Dependent Data with Vine Copulas: A Practical Guide With R (Lecture Notes in Statistics) de Claudia Czado
DescripciĆ³n - ReseƱa del editor 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 readersā 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 of vine copulas. Accordingly, it provides the necessary background in multivariate statistics and copula theory for exploratory data tools, so that readers only need a basic grasp of statistics and probability. Contraportada 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 readersā 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 of vine copulas. Accordingly, it provides the necessary background in multivariate statistics and copula theory for exploratory data tools, so that readers only need a basic grasp of statistics and probability. BiografĆa del autor Claudia Czado is an Associate Professor of Applied Mathematical Statistics at the Technical University of Munich, Germany. Her research interests are in the dependence modeling of complex data structures, copula based quantile regression, generalized linear models and computational Bayesian methods, and the applications of these methods. She holds a Ph.D. in Operations Research and Industrial Engineering from Cornell University, USA.
Detalles del Libro
- Name: Analyzing Dependent Data with Vine Copulas: A Practical Guide With R (Lecture Notes in Statistics)
- Autor: Claudia Czado
- Categoria: Libros,Libros universitarios y de estudios superiores,Medicina y ciencias de la salud
- TamaƱo del archivo: 16 MB
- Tipos de archivo: PDF Document
- Descargada: 637 times
- Idioma: EspaƱol
- Archivos de estado: AVAILABLE
[Download] Analyzing Dependent Data with Vine Copulas: A Practical Guide With R (Lecture Notes in Statistics) de Claudia Czado libros ebooks
Analyzing dependent data with vine copulas a practical this textbook provides a stepbystep introduction to vine copulas their statistical inference and applications focusing on statistical estimation and selection methods for data applications it includes numerous exercises and examples and uses the statistical software r for computations
Reliability evaluation and importance analysis of different from the dependence between two failure modes the dependence of multiple failure modes is more complicated in this paper on the basis of vine copula function which is a flexible tool to describe the multivariate dependence the dependence of multiple failure modes of the structural systems is mainly studied and analyzed
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