Predictive Modeling Applications in Actuarial Science
 Volume 1
 Introduction
 Predictive Modeling Foundations
 Predictive Modeling Methods
 Bayesian and Mixed Modeling
 Longitudinal Modeling
 Volume 2
 Generalized Linear Model
 Extensions of the Generalized Linear Model
 Unsupervised Predictive Modeling Methods

Applications on Current Problems in Actuarial Science
 Chapter 8  The Predictive Distribution of Loss Reserve Estimates over a Finite Time Horizon
 Chapter 9  Finite Mixture Model and Workersâ€™ Compensation LargeLoss Regression Analysis
 Chapter 10  A Framework for Managing Claim Escalation Using Predictive Modeling
 Chapter 11  Predictive Modeling for UsageBased Auto Insurance
Chapter 8  Linear Mixed Models
Authors
Katrien Antonio  University of Amsterdam and KU Leuven
katrien.antonio@econ.kuleuven.be
Yanwei Zhang  University of Southern California
actuaryzhang10@gmail.com
Chapter Preview
We give a general discussion of linear mixed models and continue with illustrating specific actuarial applications of this type of models. Technical details on linear mixed models follow: model assumptions, specifications, estimation techniques and methods of inference. We include three worked out examples with the R lme4 package and use ggplot2 for the graphs.
Data  R Code 
Counts Workers Data  
Credit Dannenburg Data  Credit Dannenburg Code 
Loss Workers Data  Work Comp Loss Model 
My Hachemeister Data  Hachemeister Code 
wcLoss  Workers Freq Model 