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Analyzing Dependent Data with Vine Copulas

Analyzing Dependent Data with Vine Copulas


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About the Book

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.


About the Author:

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.


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Product Details
  • ISBN-13: 9783030137847
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Height: 234 mm
  • No of Pages: 242
  • Series Title: Lecture Notes in Statistics
  • Sub Title: A Practical Guide with R
  • Width: 156 mm
  • ISBN-10: 3030137848
  • Publisher Date: 15 May 2019
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Spine Width: 15 mm
  • Weight: 440 gr


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