Date Approved

2012

Degree Type

Open Access Senior Honors Thesis

Department

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.

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