Asymptotic normality of improved weighted empirical distribution functions
Authors:
R. Maĭboroda and O. Kubaĭchuk
Translated by:
S. Kvasko
Journal:
Theor. Probability and Math. Statist. 69 (2004), 95-102
MSC (2000):
Primary 62G30; Secondary 62G20
DOI:
https://doi.org/10.1090/S0094-9000-05-00617-4
Published electronically:
February 8, 2005
MathSciNet review:
2110908
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Abstract | References | Similar Articles | Additional Information
Abstract: Weighted empirical distribution functions are often used to estimate the distributions of components in a mixture. However, weighted empirical distribution functions do not possess some properties of probability distribution functions in the case of negative weight coefficients. We consider a method allowing one to improve weighted empirical distribution functions and obtain an estimator that is a distribution function. We prove that this estimator is asymptotically normal. The limit distribution of the improved weighted empirical distribution function coincides with that of the initial estimator.
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Additional Information
R. Maĭboroda
Affiliation:
Department of Probability Theory and Mathematical Statistics, Faculty of Mechanics and Mathematics, National Taras Shevchenko University, Academician Glushkov Avenue 6, Kyiv 03127, Ukraine
Email:
mre@mechmat.univ.kiev.ua
O. Kubaĭchuk
Affiliation:
Department of Probability Theory and Mathematical Statistics, Faculty of Mechanics and Mathematics, National Taras Shevchenko University, Academician Glushkov Avenue 6, Kyiv 03127, Ukraine
Email:
linsta@akcecc.kiev.ua
Received by editor(s):
September 26, 2002
Published electronically:
February 8, 2005
Article copyright:
© Copyright 2005
American Mathematical Society