Elements of Copula Modeling with R
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Beschreibung
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.
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.
Offers an introduction to copulas and their main properties, along with the most important theoretical results Illustrates the concepts using stand-alone and reproducible R examples involving synthetic or real-world data Elaborates copula transformations, copula estimation, graphical diagnostics, statistical tests and model selection Addresses advanced topics such as the handling of ties, time series and covariates in a regression setting
Autor*in
Marius Hofert
Themen in »Elements of Copula Modeling with R«
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 quantitative finance