A Practitioner's Guide to Generalized Linear Models

Abstract
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.

Volume
February/3rd edition
Page
1 - 116
Year
2007
Keywords
predictive analytics
Syllabus year
2010
Syllabus exam
9
Categories
Financial and Statistical Methods
Statistical Models and Methods
Generalized Linear Modeling
Publications
CAS Exam Study Note
Authors
Ducan Anderson
Sholom Feldblum
Claudine Modlin
Doris Schirmacher
Ernesto Schirmacher
Neeza Thandi