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December, 1982 The Effect of Dependence on Chi Squared Tests of Fit
David S. Moore
Ann. Statist. 10(4): 1163-1171 (December, 1982). DOI: 10.1214/aos/1176345981

Abstract

Tests of fit that assume i.i.d. observations may be affected by dependence among the observations. This effect is studied for the Pearson chi squared test when the data form a stationary stochastic process. The general form of asymptotic distribution theory under the null hypothesis is outlined and examples are given. For testing fit to a specified normal law, it is shown that when observations come from a quite general class of Gaussian stationary processes, positive correlation among the observations is confounded with lack of normality.

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David S. Moore. "The Effect of Dependence on Chi Squared Tests of Fit." Ann. Statist. 10 (4) 1163 - 1171, December, 1982. https://doi.org/10.1214/aos/1176345981

Information

Published: December, 1982
First available in Project Euclid: 12 April 2007

zbMATH: 0507.62045
MathSciNet: MR673651
Digital Object Identifier: 10.1214/aos/1176345981

Subjects:
Primary: 62G10
Secondary: 62M99

Rights: Copyright © 1982 Institute of Mathematical Statistics

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Vol.10 • No. 4 • December, 1982
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