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Theory of Probability and Mathematical Statistics

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Consistency of quantile estimators in regression models with long-range dependent noise


Author: I. M. Savich
Translated by: Oleg Klesov
Original publication: Teoriya Imovirnostei ta Matematichna Statistika, tom 82 (2010).
Journal: Theor. Probability and Math. Statist. 82 (2011), 129-138
MSC (2010): Primary 62J02; Secondary 62J99
DOI: https://doi.org/10.1090/S0094-9000-2011-00832-0
Published electronically: August 4, 2011
MathSciNet review: 2790488
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Abstract: Sufficient conditions for weak consistency of the Koenker-Bassett estimator are obtained for the parameter of a nonlinear regression model with continuous time and random noise possessing the property of the long-range dependence.


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Additional Information

I. M. Savich
Affiliation: Department of Mathematical Analysis and Probability Theory, National Technical University of Ukraine “Kyiv Polytechnic Institute”, Peremogy Avenue 37, Kyiv–56 03056, Ukraine
Email: sim_ka@i.ua

DOI: https://doi.org/10.1090/S0094-9000-2011-00832-0
Keywords: Quantile estimators, consistency, nonlinear regression models, noise with long-range memory
Received by editor(s): December 1, 2009
Published electronically: August 4, 2011
Article copyright: © Copyright 2011 American Mathematical Society