Dependence modeling : vine copula handbook / editors, Dorota Kurowicka, Harry Joe.

Format:

Book

Contributor:

Kurowicka, Dorota.

Joe, Harry.

Language:

English

Subjects (All):

Copulas (Mathematical statistics).

Dependence (Statistics).

Distribution (Probability theory).

Physical Description:

1 online resource (368 p.)

Edition:

1st ed.

Place of Publication:

Hackensack, N.J. : World Scientific, 2011.

Language Note:

English

Summary:

This book is a collaborative effort from three workshops held over the last three years, all involving principal contributors to the vine-copula methodology. Research and applications in vines have been growing rapidly and there is now a growing need to collate basic results, and standardize terminology and methods. Specifically, this handbook will trace historical developments, standardizing notation and terminology, summarize results on bivariate copulae, summarize results for regular vines, and give an overview of its applications. In addition, many of these results are new and not readily

Contents:

Preface; Contents; 1. Introduction: Dependence Modeling D. Kurowicka; 2. Multivariate Copulae M. Fischer; 3. Vines Arise R. M. Cooke, H. Joe and K. Aas; 4. Sampling Count Variables with Specified Pearson Correlation: A Comparison between a Naive and a C-Vine Sampling Approach V. Erhardt and C. Czado; 5. Micro Correlations and Tail Dependence R. M. Cooke, C. Kousky and H. Joe; 6. The Copula Information Criterion and Its Implications for the Maximum Pseudo-Likelihood Estimator S. Grønneberg; 7. Dependence Comparisons of Vine Copulae with Four or More Variables H. Joe

8. Tail Dependence in Vine Copulae H. Joe9. Counting Vines O. Morales-Napoles; 10. Regular Vines: Generation Algorithm and Number of Equivalence Classes H. Joe, R. M. Cooke and D. Kurowicka; 11. Optimal Truncation of Vines D. Kurowicka; 12. Bayesian Inference for D-Vines: Estimation and Model Selection C. Czado and A. Min; 13. Analysis of Australian Electricity Loads Using Joint Bayesian Inference of D-Vines with Autoregressive Margins C. Czado, F. G ̈artner and A. Min; 14. Non-Parametric Bayesian Belief Nets versus Vines A. Hanea

15. Modeling Dependence between Financial Returns Using Pair-Copula Constructions K. Aas and D. Berg16. Dynamic D-Vine Model A. Heinen and A. Valdesogo; 17. Summary and Future Directions D. Kurowicka; Index

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

ISBN:

9786613144416

9781283144414

1283144417

9789814299886

981429988X

OCLC:

741492811