| Title | Generalized Linear Models for Insurance Data |
| Author(s) | Piet de Jong, Gillian Z. Heller |
| Publisher | Cambridge University Press |
| Year | 2008 |
| Edition | 1st edition |
| Language | English |
| Pages | 208 pages |
| ISBN | 9780521874029 |
| Genre / Domain | Actuarial Science, Statistics, Mathematics |
| Size | 1.23 MB |
| Extension | DJVU |
Summary
"Generalized Linear Models for Insurance Data" by Piet de Jong and Gillian Z. Heller is an essential text that provides a rigorous and practical introduction to generalized linear models (GLMs) tailored specifically for the insurance industry . Published by Cambridge University Press in 2008, this book fills a critical gap by focusing on GLMs within the context of insurance, addressing the unique challenges posed by insurance datasets . The authors utilize real-world data sets throughout the book, ensuring that readers can directly apply the concepts to their professional work .
At its core, the book covers all standard exponential family distributions, including Poisson, binomial, and gamma models, which are fundamental for modeling insurance claim counts, frequencies, and severities . It extends traditional GLM methodology to handle correlated data structures, a common feature in insurance data such as policyholder histories or geographic clustering . The text also discusses recent advancements that go beyond traditional GLMs, providing readers with a comprehensive toolkit for modern actuarial modeling . Key topics include strategies for model selection with large data sets and techniques for managing varying exposure times across observations .
For actuaries and practitioners, this book offers a practical and accessible guide to implementing GLMs in their daily work. It includes a wealth of exercises and practical applications to help readers strengthen their skills, with solutions and data sets available on a companion website . The book is package-independent, but the appendix includes SAS code and output examples, while R code and outputs for all examples are provided online, making it a versatile resource regardless of the reader's preferred software . This comprehensive approach equips professionals with the knowledge needed to make informed, data-driven decisions in pricing, reserving, and risk assessment .
The primary audience for this book includes actuaries, statisticians, and researchers in insurance and quantitative finance . It is also an invaluable resource for graduate students in actuarial science, statistics, and related fields . The content is designed to be accessible to those with a basic understanding of statistical modeling, while offering the depth needed for advanced practitioners .
Published by Cambridge University Press, this book benefits from a strong reputation for academic quality and rigorous peer review . It has become a standard reference in the actuarial community, praised for its focus on practical applications and its ability to bridge the gap between statistical theory and real-world insurance problems . Its clear explanations and comprehensive coverage make it an indispensable tool for anyone involved in the quantitative analysis of insurance data .
Key Features
- Provides a comprehensive introduction to GLMs specifically for insurance applications .
- Uses real-world insurance datasets throughout to illustrate key concepts .
- Covers all standard exponential family distributions: Poisson, binomial, and gamma .
- Extends methodology to handle correlated data structures in insurance .
- Discusses recent advancements beyond traditional GLMs .
- Includes strategies for model selection with large data sets .
- Features exercises and applications with solutions on a companion website .
- Provides SAS and R code examples for all applications .
- Published by Cambridge University Press, a leading academic publisher .
- Essential resource for actuaries, statisticians, and graduate students .
About Author
Piet de Jong is a distinguished professor in the Department of Actuarial Science at Macquarie University in Sydney, Australia . His research interests lie in the application of statistical methods to insurance and finance, with a particular focus on generalized linear models and their extensions . He has published extensively in leading actuarial and statistical journals and is widely recognized for his contributions to the field .
Gillian Z. Heller is a respected lecturer in the Department of Actuarial Science at Macquarie University, where she specializes in statistical modeling and its applications to insurance data . Her work focuses on the practical implementation of statistical techniques, making complex methodologies accessible to students and practitioners . Together, de Jong and Heller have created a text that combines theoretical rigor with practical relevance, making it a cornerstone of actuarial education .
Related Books
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- An Introduction to Generalized Linear Models — Annette J. Dobson and Adrian G. Barnett
- Loss Models: From Data to Decisions — Stuart A. Klugman et al.
- Actuarial Modeling: A Practical Approach — David A. Dickey et al.
- Statistical Models in Actuarial Science — R. S. P. Singh
- Generalized Linear Models for Actuaries — L. A. F. S. (Editor)
- Modern Actuarial Risk Theory — Rob Kaas et al.
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FAQ
Q : Who are the authors of this book?
R : The authors are Piet de Jong and Gillian Z. Heller, both affiliated with the Department of Actuarial Science at Macquarie University .
Q : What is the main focus of "Generalized Linear Models for Insurance Data"?
R : It provides a comprehensive guide to applying GLMs to insurance data, covering real-world datasets, standard distributions, and advanced modeling techniques .
Q : Who is the target audience for this book?
R : Actuaries, statisticians, researchers, and graduate students in actuarial science and quantitative finance .
Q : What distributions are covered in the book?
R : It covers all standard exponential family distributions, including Poisson, binomial, and gamma .
Q : Does the book include software code examples?
R : Yes, the appendix includes SAS code and output examples, while R code is provided on the companion website .
Q : What is the ISBN of the book?
R : The ISBN is 9780521874029.
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