ADVANCED LOSS MODELS

Graduate

This course is a study of the mathematics of survival models and includes some examples of parametric survival models. Topics include: tabular survival models, estimates from complete and incomplete data samples, parametric survival models, and determining the optimal parameters. Maximum likelihood estimators, derivation and properties, product limit estimators, Kaplan-Meier and Nelson-Aalen, credibility theory: limited fluctuation; Bayesian; Buhlmann; Buhlmann-Straub; empirical Bayes parameter estimation; statistical inference for loss models; maximum likelihood estimation; the effect of policy modifications; and model selection will also be discussed. Students will be expected to develop a thorough understanding through additional case study at a graduate level. This course is cross-level listed with AMS 4550. Credit cannot be received for both MCS 8560 and AMS 4550. PREREQUISITE: Admission to a graduate program in Science HOURS OF CREDIT: 3