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Elements of Copula Modeling with R

  • Marius Hofert
  • Ivan Kojadinovic
  • Martin Mächler
  • Jun Yan

Part of the Use R! book series (USE R)

Table of contents

  1. Front Matter
    Pages i-x
  2. Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan
    Pages 1-8
  3. Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan
    Pages 9-79
  4. Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan
    Pages 81-132
  5. Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan
    Pages 133-165
  6. Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan
    Pages 167-196
  7. Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan
    Pages 197-254
  8. Back Matter
    Pages 255-267

About this book

Introduction

This book introduces the main theoretical findings related to copulas and shows how statistical modeling of multivariate continuous distributions using copulas can be carried out in the R statistical environment with the package copula (among others). 

Copulas are multivariate distribution functions with standard uniform univariate margins. They are increasingly applied to modeling dependence among random variables in fields such as risk management, actuarial science, insurance, finance, engineering, hydrology, climatology, and meteorology, to name a few.

In the spirit of the Use R! series, each chapter combines key theoretical definitions or results with illustrations in R. Aimed at statisticians, actuaries, risk managers, engineers and environmental scientists wanting to learn about the theory and practice of copula modeling using R without an overwhelming amount of mathematics, the book can also be used for teaching a course on copula modeling.


Keywords

62H05, 62H12, 62H15, 62P05, 62P12 Copulas Multivariate distributions Multivariate dependance Statistical environment R R package copula Statistical modeling Statistical modeling of multivariate distributions Applications in finance and insurance Applications in engineering Applications in environmental sciences

Authors and affiliations

  • Marius Hofert
    • 1
  • Ivan Kojadinovic
    • 2
  • Martin Mächler
    • 3
  • Jun Yan
    • 4
  1. 1.Department of Statistics and Actuarial ScienceUniversity of WaterlooWaterlooCanada
  2. 2.Laboratory of Mathematics and its ApplicationsUniversity of Pau and Pays de l’AdourPauFrance
  3. 3.Seminar for StatisticsETH ZurichZurichSwitzerland
  4. 4.Department of StatisticsUniversity of ConnecticutStorrsUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-89635-9
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-89634-2
  • Online ISBN 978-3-319-89635-9
  • Series Print ISSN 2197-5736
  • Series Online ISSN 2197-5744
  • Buy this book on publisher's site