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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


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.


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

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

Primary: 62G10
Secondary: 62M99

Keywords: Chi squared tests , goodness of fit , stationary stochastic proceses

Rights: Copyright © 1982 Institute of Mathematical Statistics


Vol.10 • No. 4 • December, 1982
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