Effective Statistical Learning Methods for Actuaries I GLMs and Extensions /

• Main Authors: Denuit, Michel (Author, http://id.loc.gov/vocabulary/relators/aut), Hainaut, Donatien (http://id.loc.gov/vocabulary/relators/aut), Trufin, Julien (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Springer Actuarial Lecture Notes,
• Subjects: Actuarial science.; Statistics .; Actuarial Sciences.; Statistics for Business, Management, Economics, Finance, Insurance.

This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling,...

Table of Contents:

• Preface
• Part I: LOSS MODELS.-1. Insurance Risk Classification.-Exponential Dispersion (ED) Distributions.-3.-Maximum Likelihood Estimation.-Part II LINEAR MODELS.-4. Generalized Linear Models (GLMs)
• 5.-Over-dispersion, credibility adjustments, mixed models, and regularization.-Part III ADDITIVE MODELS
• 6 Generalized Additive Models (GAMs)
• 7. Beyond Mean Modeling: Double GLMs and GAMs for Location, Scale and Shape (GAMLSS)
• Part IV SPECIAL TOPICS
• 8. Some Generalized Non-Linear Models (GNMs)
• 9 Extreme Value Models
• References.