Predictive Modeling Applications in Actuarial Science

1. Predictive modeling in actuarial science Edward W. Frees and Richard A. Derrig
Part I. Predictive Modeling Foundations:
2. Overview of linear models Marjorie Rosenberg
3. Regression with categorical dependent variables Montserrat Guillen
4. Regression with count-dependent variables Jean-Philippe Boucher
5. Generalized linear models Curtis Gary Dean
6. Frequency and severity models Edward W. Frees
Part II. Predictive Modeling Methods:
7. Longitudinal and panel data models Edward W. Frees
8. Linear mixed models Katrien Antonio and Yanwei Zhang
9. Credibility and regression modeling Vytaras Brazauskas, Harald Dornheim and Ponmalar Ratnam
10. Fat-tailed regression models Peng Shi
11. Spatial modeling Eike Brechmann and Claudia Czado
12. Unsupervised learning Louise Francis
Part III. Bayesian and Mixed Modeling:
13. Bayesian computational methods Brian Hartman
14. Bayesian regression models Luis Nieto-Barajas and Enrique de Alba
15. Generalized additive models and nonparametric regression Patrick L. Brockett, Shuo-Li Chuang and Utai Pitaktong
16. Non-linear mixed models Katrien Antonio and Yanwei Zhang
Part IV. Longitudinal Modeling:
17. Time series analysis Piet de Jong
18. Claims triangles/loss reserves Greg Taylor
19. Survival models Jim Robinson
20. Transition modeling Bruce Jones and Weijia Wu.