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On Empirical Distribution Functions Under Auxiliary Information

2017
Being the nonparametric maximum likelihood estimator, the classical empirical distribution function is the estimator of choice for a completely unknown distribution function. As shown by Qin and Lawless in (Ann Statist 22:300–325, 1994), in the presence of some nonparametric auxiliary information about the underlying distribution function the ...
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Methods Based on the Empirical Distribution Function

2009
In this chapter a very wide class of statistical tests based on the empirical distribution function (EDF) is introduced. Among these tests we find some old tests, as the Kolmogorov-Smirnov test, but also in recent years new tests have still been added to this class. A discussion on the EDF and empirical processes has been given in Sections 2.1 and 2.2.
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On The Emperical Distribution Function

The Egyptian Statistical Journal, 1970
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