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October 1996 Asymptotic optimality of data-driven Neyman's tests for uniformity
Tadeusz Inglot, Teresa Ledwina
Ann. Statist. 24(5): 1982-2019 (October 1996). DOI: 10.1214/aos/1069362306

Abstract

Data-driven Neyman's tests resulting from a combination of eyman' smooth tests for uniformity and Schwarz's selection procedure are nvestigated. Asymptotic intermediate efficiency of those tests with respect to the Neyman-Pearson test is shown to be 1 for a large set of converging alternatives. The result shows that data-driven Neyman's tests, contrary to classical goodness-of-it tests, are indeed omnibus tests adapting well to the data at hand.

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Tadeusz Inglot. Teresa Ledwina. "Asymptotic optimality of data-driven Neyman's tests for uniformity." Ann. Statist. 24 (5) 1982 - 2019, October 1996. https://doi.org/10.1214/aos/1069362306

Information

Published: October 1996
First available in Project Euclid: 20 November 2003

zbMATH: 0905.62044
MathSciNet: MR1421157
Digital Object Identifier: 10.1214/aos/1069362306

Subjects:
Primary: 62A10, 62G05, 62G10, 62G20

Rights: Copyright © 1996 Institute of Mathematical Statistics

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Vol.24 • No. 5 • October 1996
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