Modelling Mortality with Actuarial Applications
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portes grátis
Modelling Mortality with Actuarial Applications
Richards, Stephen J.; Macdonald, Angus S.; Currie, Iain D.
Cambridge University Press
05/2018
384
Dura
Inglês
9781107045415
15 a 20 dias
740
Descrição não disponível.
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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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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