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 16  NonLinear 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 start with a discussion of model families for multilevel data outside the Gaussian framework. We continue with Generalized Linear Mixed Models (GLMMs), which enable generalized linear modeling with multilevel data. The Chapter includes highlights of estimation techniques for GLMMs, in the frequentist as well as Bayesian context. We continue with a discussion of NonLinear Mixed Models (NLMMs). The Chapter concludes with an extensive case study using a selection of R packages for GLMMs.
Data  R Code 
CountsWorkers  
WorkersFreqData  
WorkersFreqModel  
WorkersFreqModelVarSlopes  
WorkCompFreq  
getInits  
glmmBUGSExample 