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190201 ||| eng |
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|a 9783319896359
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| 100 |
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|a Hofert, Marius
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| 245 |
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|a Elements of Copula Modeling with R
|h Elektronische Ressource
|c by Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan
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| 250 |
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|a 1st ed. 2018
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2018, 2018
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| 300 |
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|a X, 267 p. 597 illus., 21 illus. in color
|b online resource
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| 505 |
0 |
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|a Preface -- Introduction -- Copulas -- Classes and Families -- Estimation -- Graphical Diagnostics, Tests and Model Selection -- Ties, Time Series and Regression -- R and Package Versions -- References -- Index
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| 653 |
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|a Mathematics in Business, Economics and Finance
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| 653 |
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|a Engineering mathematics
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| 653 |
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|a Statistics
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| 653 |
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|a Statistics in Business, Management, Economics, Finance, Insurance
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| 653 |
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|a Computer software
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| 653 |
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|a Social sciences / Mathematics
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| 653 |
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|a Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
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| 653 |
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|a Engineering / Data processing
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| 653 |
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|a Mathematical statistics / Data processing
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| 653 |
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|a Statistics and Computing
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| 653 |
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|a Mathematical Software
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| 653 |
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|a Mathematical and Computational Engineering Applications
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| 700 |
1 |
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|a Kojadinovic, Ivan
|e [author]
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| 700 |
1 |
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|a Mächler, Martin
|e [author]
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| 700 |
1 |
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|a Yan, Jun
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Use R!
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| 028 |
5 |
0 |
|a 10.1007/978-3-319-89635-9
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-89635-9?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 300,727
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| 520 |
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|a 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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