Fr. 106.00

Modelling Mortality With Actuarial Applications

English · Hardback

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Informationen zum Autor Angus S. Macdonald is Professor of Actuarial Mathematics at Heriot-Watt University, Edinburgh. He is an actuary with much experience of modeling mortality and other life histories, particularly in connection with genetics, and as a member of Continuous Mortality Investigation committees. Stephen J. Richards is an actuary and principal of Longevitas Ltd., Edinburgh, a software and consultancy firm that uses many of the models described in this book with life insurance and pension scheme clients worldwide. Iain D. Currie is an Honorary Research Fellow at Heriot-Watt University, Edinburgh. As a statistician, he was chiefly responsible for the development of the spline models described in this book, and their application to actuarial problems. Klappentext Modern mortality modelling for actuaries and actuarial students! with example R code! to unlock the potential of individual data. Zusammenfassung Actuaries modelling mortality have! until now! mostly used methods based on aggregate data. This book explains to practitioners how to build and test models based on the individual person! with plenty of example R code. Students will also find it helpful in preparation for their professional examinations. Inhaltsverzeichnis Preface; Part I. Analysing Portfolio Mortality: 1. Introduction; 2. Data preparation; 3. The basic mathematical model; 4. Statistical inference with mortality data; 5. Fitting a parametric survival model; 6. Model comparison and tests of fit; 7. Modelling features of the portfolio; 8. Non-parametric methods; 9. Regulation; Part II. Regression and Projection Models: 10. Methods of graduation I - regression models; 11. Methods of graduation II - smooth models; 12. Methods of graduation III - 2-dimensional models; 13. Methods of graduation IV - forecasting; Part III. Multiple-State Models: 14. Markov multiple-state models; 15. Inference in the Markov model; 16. Competing risks models; 17. Counting-process models; Appendix A. R commands; Appendix B. Basic likelihood theory; Appendix C. Conversion to published tables; Appendix D. Numerical integration; Appendix E. Mean and variance-covariance of a vector; Appendix F. Differentiation with respect to a vector; Appendix G. Kronecker product of two matrices; Appendix H. R functions and programs; References; Author index; Index....

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