Generalized Linear Models for Insurance Data

Generalized Linear Models for Insurance Data By Piet de Jong, Gillian Z. Heller

Generalized linear modeling is a methodology for modeling relationships between variables. It generalizes the classical normal linear model, by relaxing some of its restrictive assumptions, and provides methods for the analysis of non-normal data. The tools date back to the original article by Nelder and Wedderburn (1972) and have since become part of mainstream statistics, used in many diverse areas of application. This text presents the generalized linear model (GLM) methodology, with applications oriented to data that actuarial analysts are likely to encounter, and the analyses that they are likely required to perform.

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