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Elements of copula modeling with R

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...

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Detalles Bibliográficos
Autores principales: Hofert, Marius, Kojadinovic, Ivan, Mächler, Martin, Yan, Jun
Lenguaje:eng
Publicado: Springer 2018
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-89635-9
http://cds.cern.ch/record/2657836
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author Hofert, Marius
Kojadinovic, Ivan
Mächler, Martin
Yan, Jun
author_facet Hofert, Marius
Kojadinovic, Ivan
Mächler, Martin
Yan, Jun
author_sort Hofert, Marius
collection CERN
description 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.
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spelling cern-26578362021-04-21T18:36:37Zdoi:10.1007/978-3-319-89635-9http://cds.cern.ch/record/2657836engHofert, MariusKojadinovic, IvanMächler, MartinYan, JunElements of copula modeling with RMathematical Physics and MathematicsThis 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.Springeroai:cds.cern.ch:26578362018
spellingShingle Mathematical Physics and Mathematics
Hofert, Marius
Kojadinovic, Ivan
Mächler, Martin
Yan, Jun
Elements of copula modeling with R
title Elements of copula modeling with R
title_full Elements of copula modeling with R
title_fullStr Elements of copula modeling with R
title_full_unstemmed Elements of copula modeling with R
title_short Elements of copula modeling with R
title_sort elements of copula modeling with r
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-89635-9
http://cds.cern.ch/record/2657836
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