Modelling Mortality with Actuarial Applications
- Angus S. Macdonald, Heriot-Watt University, Edinburgh
- Stephen J. Richards, Longevitas Ltd, Edinburgh
- Iain D. Currie, Heriot-Watt University, Edinburgh
Adobe eBook Reader
Other available formats:
Looking for an evaluation copy?
This title is not currently available for evaluation. However, if you are interested in the title for your course we can consider offering an evaluation copy. To register your interest please contact email@example.com providing details of the course you are teaching.
Actuaries have access to a wealth of individual data in pension and insurance portfolios, but rarely use its full potential. This book will pave the way, from methods using aggregate counts to modern developments in survival analysis. Based on the fundamental concept of the hazard rate, Part I shows how and why to build statistical models, based on data at the level of the individual persons in a pension scheme or life insurance portfolio. Extensive use is made of the R statistics package. Smooth models, including regression and spline models in one and two dimensions, are covered in depth in Part II. Finally, Part III uses multiple-state models to extend survival models beyond the simple life/death setting, and includes a brief introduction to the modern counting process approach. Practising actuaries will find this book indispensable, and students will find it helpful when preparing for their professional examinations.Read more
- The first book to present survival analysis as a useful tool for actuaries
- Extensive use of R throughout allows actuaries to quickly apply the techniques to their own data
- The book will teach actuaries how to realise the full potential of their available data
Reviews & endorsements
'This book is an excellent companion to Actuarial Mathematics for Life Contingent Risks (Dickson, Hardy and Waters) because it provides concrete applications of the theory of survival. The authors cover a lot of ground in a friendly, accessible style with real examples. Actuaries - both students and practitioners - can learn a great deal from this book.' Ian Duncan, University of California, Santa BarbaraSee more reviews
'I taught the analysis of survival data to demographers and actuarial students for many years, and my task would have been made a great deal easier had a book like this been available. It covers the essential elements in a way that is both intellectually satisfying (starting with the fundamental concepts and building on these) and focused on the analysis of empirical data. The methods described are modern, state-of-the art approaches. Moreover, because the book provides readers with a sound understanding of the theory underlying these methods, they will be well equipped to take on board future developments, even in a fast-moving field. I can recommend this book for advanced undergraduate and Masters-level students studying actuarial science, demographic methods and related areas of statistics.' Andrew Hinde, University of Southampton
'A wonderfully comprehensive piece of work from leading experts in the field. Essential reading for anyone with an interest in longevity modelling.' Richard Willets, ReAssure Ltd.
Not yet reviewed
Be the first to review
Review was not posted due to profanity×
- Date Published: April 2018
- format: Adobe eBook Reader
- isbn: 9781108686334
- contains: 95 b/w illus. 42 tables
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
Part I. Analysing Portfolio Mortality:
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
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
Find resources associated with this titleYour search for '' returned .
Type Name Unlocked * Format Size
*This title has one or more locked files and access is given only to lecturers adopting the textbook for their class. We need to enforce this strictly so that solutions are not made available to students. To gain access to locked resources you either need first to sign in or register for an account.
These resources are provided free of charge by Cambridge University Press with permission of the author of the corresponding work, but are subject to copyright. You are permitted to view, print and download these resources for your own personal use only, provided any copyright lines on the resources are not removed or altered in any way. Any other use, including but not limited to distribution of the resources in modified form, or via electronic or other media, is strictly prohibited unless you have permission from the author of the corresponding work and provided you give appropriate acknowledgement of the source.
If you are having problems accessing these resources please email firstname.lastname@example.org
Sorry, this resource is locked