The Practitioner's Guide to Generalized Linear Models is written for the practicing actuary who would like to understand generalized linear models (GLMs) and use them to analyze insurance data. The guide is divided into three sections.
Section 1 provides a foundation for the statistical theory and gives illustrative examples and intuitive explanations which clarify the theory. The intuitive explanations build upon more commonly understood actuarial methods such as linear models and the minimum bias procedures.
Section 2 provides practical insights and realistic model output for each stage of a GLM analysis - including data preparation and preliminary analyses, model selection and iteration, model refinement and model interpretation. This section is designed to boost the actuary's confidence in interpreting GLMs and applying them to solve business problems.
Section 3 discusses other topics of interest relating to GLMs such as retention modeling and scoring algorithms.