Spatial cross-sectional credibility models with general dependence structure among risks

Author: 
Date created: 
2013-01-18
Identifier: 
etd7657
Keywords: 
Credibility premium
Spatial statistics
Dependence
Regression credibility model
Structural parameter estimation
Abstract: 

Credibility models with general dependence structure among risks and conditional spatial cross-sectional dependence are studied in this project. Predictors of future losses for a Buhlmann-type credibility model under both types of dependence are derived by minimizing the quadratic loss function, and this is further extended to Buhlmann-Straub and regression credibility model formulations. Non-parametric estimators of structural parameters of various models under a spatial statistics context are also considered especially for the case of equal unconditional means. An example with crop insurance losses is studied to illustrate the use of predictors and estimators proposed in this project. Finally, the performance of the predictors and estimators are evaluated in a simulation study.

Document type: 
Graduating extended essay / Research project
Rights: 
Copyright remains with the author. The author granted permission for the file to be printed and for the text to be copied and pasted.
File(s): 
Supervisor(s): 
Yi Lu
Department: 
Science: Department of Statistics and Actuarial Science
Thesis type: 
(Project) M.Sc.
Statistics: