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

Thumbnail Image

Files

Asymptotic normality of nearest neighbor regression function estimates based on nonstationary dependent observations final.pdf (2.74 MB)
Can’t use the file because of accessibility barriers? Contact us with the title of the item, permanent link, and specifics of your accommodation need.

Date

1995

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

American Journal of Mathematical and Management Sciences

Permanent Link

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.

Description

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.

Journal

DOI

https://doi.org/10.1080/01966324.1995.10737400

Link(s) to data and video for this item

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

Relation

Rights

Type

Article

Collections

Madan Lal Puri Collection