Non-Fiction Books:

International Series on Actuarial Science

Format

Hardback

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International Series on Actuarial Science by Piet De Jong
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Description

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.

Author Biography

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. 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.
Release date Australia
February 28th, 2008
Country of Publication
United Kingdom
Illustrations
Worked examples or Exercises; 43 Tables, unspecified; 4 Halftones, unspecified; 30 Line drawings, unspecified; 5 Line drawings, color
Imprint
Cambridge University Press
Pages
208
Dimensions
152x231x15
ISBN-13
9780521879149
Product ID
2501652

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