Bayesian Logistic Regression Models for Credit Scoring by Gregg Webster

Acknowledgements 
 
Thank you to my parents, Robert and Debra Webster for their constant love and support 
throughout my studies. This research is dedicated to them.
Thank you to my supervisor, Professor Sarah Radloff for her guidance throughout my 
research. Your helpfulness and support is highly appreciated.
Thank you to my friends and family for their support and input. Another thank you goes out 
to all the staff and students of the Rhodes Statistics department. A particular thank you goes 
to Tafadzwa Mutengwa for all the help, laughs and hard work we did together. 
This research was possible through the assistance from the Henderson Rhodes University 
Prestigious Scholarship and is hereby acknowledged.

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5 
Table of Contents 
 
Declaration
……………………………………………………………………………………ii
 
Abstract
………………………………………………………………………………………iii 
Acknowledgments
…………………………………………………………………………...iv
 
Table of Contents
.……………………………………………………………………………v
 
List of Figures
………………………………………………………………………………viii 
List of Tables
......……………………………………………………………………………..x 
 
Chapter 1: Introduction 
1.1 Context of the Research
……………………………………………………………….....1 
1.2 Objectives of the Study
………………………………………………………………......2
 
1.3 Organization of the Study
……………………………………………………………......2
 
 
Chapter 2: Literature Review 
2.1 History of Credit Scoring
………………………………………………………………..3
 
2.2 Overview of Credit Scoring and Credit Scoring Methods
………………………….....4 
2.3 Markov Chain Monte Carlo Methods
…………………………………………………..6