PARAMETRIC AND NONPARAMETRIC TESTS FOR DEPENDENT DATA

PARAMETRIC AND NONPARAMETRIC TESTS FOR DEPENDENT DATA ABSTRACT: Simulation and analytical results show that ignoring serial dependence can have serious effects on the performance of the t, sign, and Wilcoxen tests. In particular, the true significance levels of these tests are altered significantly from the intended nominal levels. Modifications for these tests are given and shown to have the correct significance levels. Furthermore, an estimate of serial correlation is suggested for binary data and evaluated by simulation. An application to the toxic contaminants data from the Niagara River concludes the paper. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the American Water Resources Association Wiley

PARAMETRIC AND NONPARAMETRIC TESTS FOR DEPENDENT DATA

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Publisher
Wiley
Copyright
Copyright © 1988 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1093-474X
eISSN
1752-1688
D.O.I.
10.1111/j.1752-1688.1988.tb00901.x
Publisher site
See Article on Publisher Site

Abstract

ABSTRACT: Simulation and analytical results show that ignoring serial dependence can have serious effects on the performance of the t, sign, and Wilcoxen tests. In particular, the true significance levels of these tests are altered significantly from the intended nominal levels. Modifications for these tests are given and shown to have the correct significance levels. Furthermore, an estimate of serial correlation is suggested for binary data and evaluated by simulation. An application to the toxic contaminants data from the Niagara River concludes the paper.

Journal

Journal of the American Water Resources AssociationWiley

Published: Jun 1, 1988

References

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