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Generalized Linear Models for Insurance Data


Part of International Series on Actuarial Science

  • Date Published: February 2008
  • availability: Available
  • format: Hardback
  • isbn: 9780521879149

£ 92.99

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About the Authors
  • 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.

    • 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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    Product details

    • Date Published: February 2008
    • format: Hardback
    • isbn: 9780521879149
    • length: 208 pages
    • dimensions: 231 x 152 x 15 mm
    • weight: 0.43kg
    • contains: 34 b/w illus. 5 colour illus. 43 tables 25 exercises
    • availability: Available
  • 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

  • Resources for

    Generalized Linear Models for Insurance Data

    Piet de Jong, Gillian Z. Heller

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  • Authors

    Piet de Jong, Macquarie University, Sydney
    Gillian Heller is Associate Professor of Statistics at Macquarie University. She has been teaching GLM to actuarial students for the past ten years, and has given several outside courses on GLMs to research analysts in insurance companies.

    Gillian Z. Heller, Macquarie University, Sydney
    Piet de Jong is Professor of Actuarial Studies at Macquarie University. His research interests lie mainly in time series analysis and forecasting as well as actuarial areas, and he has consulted widely in the insurance and forecasting areas in both Australia and North America.

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