Title

Zero-Inflated Poisson Model of Claims Frequencies Using a Maximum Likelihood and a Bayesian Approach

Author

Ricky Dixon

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematics

Date of Award

Summer 2022

Abstract

A zero-inflated Poisson model is applied to analyze claims data sets found in literature from various sources. Maximum likelihood estimation and Bayesian approaches are used to analyze the data and the results of each method are compared. A Metropolis-Hastings Markov chain Monte Carlo algorithm is used to simulate the posterior distribution of the model parameters in the Bayesian approach. Original scripts are written in R to implement the methods. Results from the maximum likelihood and Bayesian implementations are compared.

Advisor

Thomas Boucher

Subject Categories

Mathematics | Physical Sciences and Mathematics

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