A Comparison of Various Non-Parametric Discriminating Procedures When the Populations Are Bivariate Exponentials
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Authors
Lieberman, Jay Edward
Subjects
Non-parametric discriminating procedures
Bivariate negative exponential populations
Bivariate negative exponential populations
Advisors
Borsting, Jack
Date of Issue
1969-12
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
A comparison of the error probabilities for various discriminating rules is performed in the two population cases when nothing is known of the populations other than they are bivariate negative exponential. In most cases, the absolute difference between the error probabilities for each function was very small. However, the Euclidean distance function consistently performed as well as, and sometimes superior to any of the others studied in the this thesis.
Type
Thesis
Description
Series/Report No
Department
Department of Operations Analysis
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.