Generalized Linear Models for Insurance Data
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This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.Read more
- Tailored to needs of actuaries
- All techniques illustrated on real data sets relevant to insurance
- Exercises and data-based practicals consolidate skills
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"I would recommend such a book to my students without hesitation."
Cho-Jieh Chen, Journal of the American Statistical Association
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- Date Published: April 2008
- format: Adobe eBook Reader
- isbn: 9780511380983
- contains: 34 b/w illus. 5 colour illus. 43 tables 25 exercises
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
1. Insurance data
2. Response distributions
3. Exponential family responses and estimation
4. Linear modeling
5. Generalized linear models
6. Models for count data
7. Categorical responses
8. Continuous responses
9. Correlated data
10. Extensions to the Generalized linear model
Appendix 1. Computer code and output
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