Applications of assignment algorithms to nonparametric tests for homogeneity
Loading...
Authors
Ruth, David M.
Subjects
Nonparametric test
distribution-free test
non-bipartite matching
bipartite matching
change point
distribution-free test
non-bipartite matching
bipartite matching
change point
Advisors
Koyak, Robert
Date of Issue
2009-09
Date
September 2009
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
We propose new nonparametric statistical tests to identify whether each element in a sequence of independent multivariate observations is drawn from a common probability distribution or if some distributional change has occurred over the course of the sequence. Each test is formulated using matching techniques based on distances between observations. These tests are capable of detecting changes of quite general nature, and, unlike most similar tests, they require no distribution assumptions or any prior separation of the data into hypothetical pre- and post-change subsets. We derive a central limit theorem for one of the tests and an exact distribution for another. A third culminating test, which is a cumulative sum of statistics on a collection of orthogonal matchings associated with the observation sequence, exhibits noteworthy power to detect whether a distributional change has occurred. We examine the performance of the tests by computer simulation and compare results to a state-of-the-art parametric competitor.
Type
Thesis
Description
Series/Report No
Department
Operations Research
Organization
Identifiers
NPS Report Number
Sponsors
Funding
Format
xviii, 127 p. ; 28 cm.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.