Asymptotic Normality of Nearest Neighbor Regression Function Estimates Based on Nonstationary Dependent Observations

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https://www.tandfonline.com/doi/abs/10.1080/01966324.1995.10737400

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Date

1995

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American Journal of Mathematical and Management Sciences

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https://hdl.handle.net/2022/22263

Abstract

In this paper the convergence of the regression function estimators and the central limit theorem for these estimators are proved for the case when the underlying sequence of random variables is dependent and nonstationary.

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Offprint, publisher's version

Keywords

regression function, nearest neighbor regression function estimates, absolute regularity, φ–mixing, strong mixing, convergences in law

Citation

Puri, M. L. “Asymptotic normality of nearest neighbor regression function estimates based on nonstationary dependent observations.” American Journal of Mathematical and Management Sciences (1995), Volume 15, 255–290. Co-author: Michel Harel.

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DOI

https://doi.org/10.1080/01966324.1995.10737400

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This work may be protected by copyright unless otherwise stated.

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Madan Lal Puri Collection