The Annals of Statistics

Weak Convergence of the Sample Distribution Function when Parameters are Estimated

J. Durbin

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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.

Article information

Source
Ann. Statist. Volume 1, Number 2 (1973), 279-290.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
http://projecteuclid.org/euclid.aos/1176342365

Digital Object Identifier
doi:10.1214/aos/1176342365

Mathematical Reviews number (MathSciNet)
MR359131

Zentralblatt MATH identifier
0256.62021

JSTOR
links.jstor.org

Citation

Durbin, J. Weak Convergence of the Sample Distribution Function when Parameters are Estimated. Ann. Statist. 1 (1973), no. 2, 279--290. doi:10.1214/aos/1176342365. http://projecteuclid.org/euclid.aos/1176342365.


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