Date Approved
2012
Degree Type
Open Access Senior Honors Thesis
Department or School
Economics
First Advisor
Dr. Ovidiu Calin
Second Advisor
Dr. Kemper Moreland
Abstract
This thesis is a formal presentation of entropy and related principles as they relate to probability theory. The central focus is on the mathematical definition of entropy, and on methods for obtaining maximum entropy distributions. Transformations which preserve the entropy of a probability density function are also developed. Entropy is a measure of uncertainty, and a maximum entropy distributions has the desirable property of maximizing uncertainty for all unknown information of a given phenomenon.
Recommended Citation
Williams, Jonathan P., "Entropy and related principles" (2012). Senior Honors Theses and Projects. 303.
https://commons.emich.edu/honors/303