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March, 1973 Weak Convergence of the Sample Distribution Function when Parameters are Estimated
J. Durbin
Ann. Statist. 1(2): 279-290 (March, 1973). DOI: 10.1214/aos/1176342365

Abstract

The weak convergence of the sample df is studied under a given sequence of alternative hypotheses when parameters are estimated from the data. For a general class of estimators it is shown that the sample df, when normalised, converges weakly to a specified normal process. The results are specialised to the case of efficient estimation.

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J. Durbin. "Weak Convergence of the Sample Distribution Function when Parameters are Estimated." Ann. Statist. 1 (2) 279 - 290, March, 1973. https://doi.org/10.1214/aos/1176342365

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Published: March, 1973
First available in Project Euclid: 12 April 2007

zbMATH: 0256.62021
MathSciNet: MR359131
Digital Object Identifier: 10.1214/aos/1176342365

Rights: Copyright © 1973 Institute of Mathematical Statistics

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Vol.1 • No. 2 • March, 1973
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