Analyzing Dependent Data With Vine Copulas

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Analyzing Dependent Data with Vine Copulas

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 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.
Dependence Modeling

Author: Dorota Kurowicka
language: en
Publisher: World Scientific Publishing Company Incorporated
Release Date: 2011
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 (1) trace historical developments, standardizing notation and terminology, (2) summarize results on bivariate copulae, (3) summarize results for regular vines, and (4) give an overview of its applications. In addition, many of these results are new and not readily available in any existing journals. New research directions are also discussed.
Multivariate Frequency Analysis of Hydro-Meteorological Variables

Multivariate Frequency Analysis of Hydro-Meteorological Variables: A Copula-Based Approach provides comprehensive and detailed descriptions of the approaches and techniques used in multivariate frequency analysis (including, but not limited to copula functions), with illustrative examples and real-life case studies provided. The book presents all background material and new developments in one place, presenting the material in a homogeneous and pedagogical way in order to allow students, engineers and researchers to access and efficiently use all information surrounding this topic. This reference can be used as a guide to apply the available and recent approaches to evaluate hydro-meteorological risks, to design hydraulic structures, in teaching (faculty members), and as a literature review to go to the next steps in research projects (graduate students and postdocs). - Presents methods for analysis of hydro-meteorological risks followed by illustrative examples based on real life data sets - Provides definitions throughout on all new topics and key terms - Includes case studies and real-life examples covering a variety of situations and showing how this work can be applied in the reader's own work