New Zealand Statistical Association

NZSA 2009

Victoria University of Wellington

Xiaomei Li

Victoria University of Wellington

Computational model selection for the Poisson regression model

The task of statistical model selection is to choose a parsimonious model from a collection of models, which gives the best approximation to the observed data. The ultimate objective for this project is to illustrate the non-Bayesian and Bayesian approaches in computational model selection for the Poisson regression model. We developed three commonly used model selection methods by using R and WinBUGS. They are developed based on hypothesis testing, deviance, Bayesian approach, and information criterion. Also, we compare the results which we obtain from the different approaches.
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