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＜電子ブック＞
Elements of Copula Modeling with R / by Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan
(Use R!. ISSN:21975744)

版	1st ed. 2018.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2018
大きさ	X, 267 p. 597 illus., 21 illus. in color : online resource
著者標目	*Hofert, Marius author Kojadinovic, Ivan author Mächler, Martin author Yan, Jun author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Mathematical statistics—Data processing LCSH:Social sciences—Mathematics LCSH:Engineering mathematics LCSH:Engineering—Data processing LCSH:Computer software FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences FREE:Statistics and Computing FREE:Mathematics in Business, Economics and Finance FREE:Mathematical and Computational Engineering Applications FREE:Mathematical Software
一般注記	Preface -- Introduction -- Copulas -- Classes and Families -- Estimation -- Graphical Diagnostics, Tests and Model Selection -- Ties, Time Series and Regression -- R and Package Versions -- References -- Index 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 HTTP:URL=https://doi.org/10.1007/978-3-319-89635-9

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