College - Author 1
College of Science and Mathematics
Department - Author 1
Statistics Department
Degree Name - Author 1
BS in Statistics
Date
9-2012
Primary Advisor
Samuel Frame, Steve Rein
Abstract/Summary
When loglinear models are applied to count data the issue of over-dispersion often arises. Moment and maximum likelihood estimation methods in accounting for over-dispersion are widely used because they allow for model checking tools such as Chi-square, F, and likelihood ratio tests. Here is a comparison between R functions that each uses one method; glm.nb uses MLE, and glm.poisson.disp uses MME. The Index of Dissimilarity and visual model selection (ECDF plots) are also incorporated. These are applied to sales data using product and customer information compiled over the last five years that was generously provided by an e-commerce company.
URL: https://digitalcommons.calpoly.edu/statsp/28
Included in
Applied Statistics Commons, Categorical Data Analysis Commons, E-Commerce Commons, Statistical Models Commons