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December, 1992 Asymptotic Comparison of Cramer-von Mises and Nonparametric Function Estimation Techniques for Testing Goodness-of-Fit
R. L. Eubank, V. N. LaRiccia
Ann. Statist. 20(4): 2071-2086 (December, 1992). DOI: 10.1214/aos/1176348903

Abstract

Two new statistics for testing goodness-of-fit are derived from the viewpoint of nonparametric density estimation. These statistics are closely related to the Neyman smooth and Cramer-von Mises statistics but are shown to have superior properties both through asymptotic and small sample analyses. Comparison of the proposed tests with the Cramer-von Mises statistic requires the development of a novel technique for comparing tests that are capable of detecting local alternatives converging to the null at different rates.

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R. L. Eubank. V. N. LaRiccia. "Asymptotic Comparison of Cramer-von Mises and Nonparametric Function Estimation Techniques for Testing Goodness-of-Fit." Ann. Statist. 20 (4) 2071 - 2086, December, 1992. https://doi.org/10.1214/aos/1176348903

Information

Published: December, 1992
First available in Project Euclid: 12 April 2007

zbMATH: 0769.62033
MathSciNet: MR1193326
Digital Object Identifier: 10.1214/aos/1176348903

Subjects:
Primary: 62G10
Secondary: 62E20

Rights: Copyright © 1992 Institute of Mathematical Statistics

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Vol.20 • No. 4 • December, 1992
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