Elements of Copula Modeling with R

• Κύριοι συγγραφείς: Hofert, Marius (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Kojadinovic, Ivan (http://id.loc.gov/vocabulary/relators/aut), Mächler, Martin (http://id.loc.gov/vocabulary/relators/aut), Yan, Jun (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Use R!,
• Θέματα: Statistics .; Economics, Mathematical .; Applied mathematics.; Engineering mathematics.; Computer software.; Statistics for Business, Management, Economics, Finance, Insurance.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.; Statistics and Computing/Statistics Programs.; Quantitative Finance.; Mathematical and Computational Engineering.; Mathematical Software.

 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. 

 Preface -- Introduction -- Copulas -- Classes and Families -- Estimation -- Graphical Diagnostics, Tests and Model Selection -- Ties, Time Series and Regression -- R and Package Versions -- References -- Index.