Publication Date

2017

Document Type

Dissertation/Thesis

First Advisor

Ebrahimi, Nader B.

Degree Name

M.S. (Master of Science)

Department

Department of Statistics

LCSH

Statistics

Abstract

This research explores parametric and nonparametric similarities and disagreements between variance and the information theoretic measure of entropy, specifically Renyi's entropy. A history and known relationships of the two different uncertainty measures is examined. Then, twenty discrete and continuous parametric families are tabulated with their respective variance and Renyi entropy functions ordered to understand the behavior of these two measures of uncertainty. Finally, an algorithm for variable selection using Renyi's Quadratic Entropy and its kernel estimation is explored and compared to other popular selection methods using real data.

Comments

Advisors: Nader Ebrahimi.||Committee members: Alan Polansky; Duchwan Ryu.||Includes bibliographical references.||Includes illustrations.

Extent

29 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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