Analyzing Dependent Data with Vine Copulas A Practical Guide With R /

• Main Author: Czado, Claudia (Author, http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Lecture Notes in Statistics, 222
• Subjects: Statistics .; Big data.; Statistical Theory and Methods.; Statistics for Business, Management, Economics, Finance, Insurance.; Statistics for Life Sciences, Medicine, Health Sciences.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.; Big Data/Analytics.; Statistics and Computing/Statistics Programs.

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...

Table of Contents:

• Preface
• Multivariate Distributions and Copulas
• Dependence Measures
• Bivariate Copula Classes, Their Visualization and Estimation
• Pair Copula Decompositions and Constructions
• Regular Vines
• Simulating Regular Vine Copulas and Distributions
• Parameter Estimation in Regular Vine Copulas
• Selection of Regular Vine Copula Models
• Comparing Regular Vine Copula Models
• Case Study: Dependence Among German DAX Stocks
• Recent Developments in Vine Copula Based Modeling
• Indices.