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| Piet de Jong, Gillian Z. Heller | ||||
| Cambridge University Press | ||||
| 2008 | ||||
| English | ||||
| 208 pages | ||||
| 1.23 MB | ||||
| DJVU | ||||
[tab] [content title="Summary"] This book is essential for actuaries seeking to understand generalized linear models (GLMs) specifically for insurance applications. GLMs play a crucial role in the insurance industry, aiding in key decision-making processes. Unlike previous texts, this book focuses on GLMs within the context of insurance, addressing challenges unique to insurance data.Utilizing real insurance data sets, the book rigorously explores GLMs, covering all standard exponential family distributions. It also extends the methodology to accommodate correlated data structures and discusses recent advancements that go beyond traditional GLMs. Key topics include model selection with large data sets and managing varying exposure times.The book features exercises and practical applications to help readers strengthen their skills, with solutions and data sets available on a companion website. While the content is package-independent, the appendix includes SAS code and output examples, along with R code and outputs for all examples provided on the website. This comprehensive approach makes it an invaluable resource for actuaries in the field. [/content] [content title="Content"] [/content] [content title="Author(s)"] [/content] [/tab]
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