Elements of Copula Modeling with R

✍ Scribed by Marius Hofert, Ivan Kojadinovic, Martin Machler, Jun Yan

• Publisher: Springer
• Year: 2018
• Tongue: English
• Leaves: 274
• Series: Use R
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-x
Introduction (Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan)....Pages 1-8
Copulas (Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan)....Pages 9-79
Classes and Families (Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan)....Pages 81-132
Estimation (Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan)....Pages 133-165
Graphical Diagnostics, Tests, and Model Selection (Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan)....Pages 167-196
Ties, Time Series, and Regression (Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan)....Pages 197-254
Back Matter ....Pages 255-267

✦ Subjects

Statistics, Copulas, R