Generalized Linear Models for Insurance Data (International Series on Actuarial Science) [Hardcover]

Piet de Jong (Author), Gillian Z. Heller (Author)

Book Description

Publication Date: March 17, 2008 | ISBN-10: 0521879140 | ISBN-13: 978-0521879149

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.

Editorial Reviews

Review

"I would recommend such a book to my students without hesitation."
Cho-Jieh Chen, Journal of the American Statistical Association

Book Description

Actuaries should have the tools they need. Practical and rigorous, this books introduces GLMs in the actuarial context. All techniques are illustrated on data sets relevant to insurance. Exercises and data-based practicals let readers consolidate skills. SAS code and output, data sets, exercise solutions on website.

See all Editorial Reviews

Product Details

• Hardcover: 206 pages
• Publisher: Cambridge University Press (March 17, 2008)
• Language: English
• ISBN-10: 0521879140
• ISBN-13: 978-0521879149
• Product Dimensions: 9 x 6 x 0.5 inches
• Shipping Weight: 1.1 pounds (View shipping rates and policies)
• Average Customer Review: 3.5 out of 5 stars  See all reviews (2 customer reviews)
• Amazon Best Sellers Rank: #751,316 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

13 of 16 people found the following review helpful:

2.0 out of 5 stars Feels like someone's lecture notes and needs a lecturer to explain, September 29, 2008

By 

Genevieve Hayes (Australia) - See all my reviews
(REAL NAME)   

This review is from: Generalized Linear Models for Insurance Data (International Series on Actuarial Science) (Hardcover)

I have recently completed a PhD in Actuarial Studies that involved the use of Generalized Linear Models (GLMs) to describe Life Insurance data and I have also taught GLMs to a group of Actuarial Studies students in the context of using them to describe General Insurance (aka non-life insurance or property and casualty insurance) data. From the point of view of a researcher and of an educator, I consider this book to be lacking. To me, "Generalized Linear Models for Insurance Data" feels like a set of lecture notes that would probably make sense if you attended lectures to hear the lecturer explain them, but aren't all that clear to those students who decide to skip class (given that the two authors both teach in universities, there is a good chance that this is, in fact, true).

This book can essentially be divided into two sections: the first 80 pages of the book give the background theory to generalized linear models; and the remaining 116 pages apply this theory to insurance examples. Having worked with GLMs for many years now, the first section of the book made sense to me, but I suspect that a new-comer to this material would find some parts difficult to understand. Very little detail is given on some of the more important topics; no examples are given within this initial section; and concepts that are essentially visual in nature (such as diagnostic plots) are not illustrated with graphs. The second half of the book is an improvement on the first half, with examples and illustrations making up a substantially chunk of the 116 pages. Yet, again, I feel that this section could have benefited by the concepts being discussed in greater detail. From my research and teaching, I know that, for many of these topics, de Jong and Heller have only coasted along the surface of the available information.

Exercises are given at the end of each chapter of this book, and the solutions to these can be found on the books companion website, as can the data sets used throughout this book. Some SAS code for fitting many of the models discussed in the book is given in an appendix at the back of the book, although this code is just for fitting the basic models (not for producing diagnostic plots), and is only really of use if you happen to use SAS (which I don't - I would have preferred R code, which has the advantage of being open-source, so accessible by all).

5.0 out of 5 stars Great book on using GLM in insurance business, September 29, 2011

By 

Klemen Vidic (Domžale, Slovenia) - See all my reviews
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This review is from: Generalized Linear Models for Insurance Data (International Series on Actuarial Science) (Kindle Edition)

This is a great book on usage of glm in insurance business. It is not the book for learning theory of glm as the other review is correctly pointing out. It gives hands on experience and examples are great.