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Modelling Mortality with Actuarial Applications
Buch von Angus S. Macdonald (u. a.)
Sprache: Englisch

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Beschreibung
Modern mortality modelling for actuaries and actuarial students, with example R code, to unlock the potential of individual data.
Modern mortality modelling for actuaries and actuarial students, with example R code, to unlock the potential of individual data.
Über den 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.
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.
Details
Erscheinungsjahr: 2019
Fachbereich: Kommunikationswissenschaften
Genre: Medienwissenschaften
Rubrik: Wissenschaften
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781107045415
ISBN-10: 110704541X
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Macdonald, Angus S.
Richards, Stephen J.
Currie, Iain D.
Hersteller: Cambridge University Press
Maße: 235 x 157 x 25 mm
Von/Mit: Angus S. Macdonald (u. a.)
Erscheinungsdatum: 08.03.2019
Gewicht: 0,708 kg
Artikel-ID: 110444695
Über den 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.
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.
Details
Erscheinungsjahr: 2019
Fachbereich: Kommunikationswissenschaften
Genre: Medienwissenschaften
Rubrik: Wissenschaften
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781107045415
ISBN-10: 110704541X
Sprache: Englisch
Ausstattung / Beilage: HC gerader Rücken kaschiert
Einband: Gebunden
Autor: Macdonald, Angus S.
Richards, Stephen J.
Currie, Iain D.
Hersteller: Cambridge University Press
Maße: 235 x 157 x 25 mm
Von/Mit: Angus S. Macdonald (u. a.)
Erscheinungsdatum: 08.03.2019
Gewicht: 0,708 kg
Artikel-ID: 110444695
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