| Description |
1 online resource (638 pages) : illustrations, tables |
| Series |
Chapman & Hall/CRC the R Series |
|
Chapman & Hall/CRC the R series (CRC Press)
|
| Bibliography |
Includes bibliographical references. |
| Contents |
1. Introduction -- Part I: Methodology -- 2. Standard Statistical Inference -- 3. Bayesian Philosophy -- 4. Statistical Learning -- 5. Spatial Analysis -- 6. Reinsurance and Extremal Events -- Part II: Life Insurance -- 7. Life Contingencies -- 8. Prospective Life Tables -- 9. Prospective Mortality Tables and Portfolio Experience -- 10. Survival Analysis -- Part III: Finance -- 11. Stock Prices and Time Series -- 12. Yield Curves and Interest Rates Models -- 13. Portfolio Allocation -- Part IV: Non-Life Insurance -- 14. General Insurance Pricing -- 15. Longitudinal Data and Experience Rating -- 16. Claims Reserving and IBNR. |
| Summary |
"This book aims to provide a broad introduction to computational aspects of actuarial science, in the R environment. We assume that the reader is either learning, or is familiar with actuarial science. It can be seen as a companion to standard textbooks on actuarial science. This book is intended for various audiences: students, researchers, and actuaries. As explained in cite Kendrick et al. (2006) (discussing the importance of computational economics) \our thesis is that computational economics o ers a way to improve this situation and to bring new life into the teaching of economics in colleges and universities ... computational economics provides an opportunity for some students to move away from too much use of the lecture-exam paradigm and more use of a laboratorypaper paradigm in teaching under graduate economics. This opens the door for more creative activity on the part of the students by giving them models developed by previous generations and challenging them to modify those models." Based on the assumption that the same holds for computational actuarial science, we decided to publish this book. As claimed by computational scientists, computational actuarial science might simply refer to modern actuarial science methods. Computational methods started probably in the 1950s with Dwyer (1951) and von Neumann (1951). The rst one emphasized the importance of linear computations, and the second one the importance of massive computations, using random number generations (and Monte Carlo methods), while (at that time) access to digital computers was not widespread"-- Provided by publisher |
| Subject |
Actuarial science.
|
|
Actuariat. |
|
Actuarial science |
| Added Author |
Charpentier, Arthur, editor.
|
|
Antonio, Katrien, contributor.
|
| Other Form: |
Print version: Computational actuarial science with R. Boca Raton, Florida : CRC Press, ©2015 xxxi, 604 pages Chapman & Hall/CRC the R series. 9781466592599 |
| ISBN |
9781466592605 (e-book) |
|
1466592605 (e-book) |
|
1322637547 |
|
9781322637549 |
|
1466592591 |
|
9781466592599 |
|
More Resources