Campus Units

Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

1-25-2019

Journal or Book Title

Journal of the Korean Statistical Society

DOI

10.1016/j.jkss.2019.01.001

Abstract

We propose a flexible nonparametric estimation of a variance function from a one-dimensional process where the process errors are nonstationary and correlated. Due to nonstationarity a local variogram is defined, and its asymptotic properties are derived. We include a bandwidth selection method for smoothing taking into account the correlations in the errors. We compare the proposed difference-based nonparametric approach with Anderes and Stein(2011)’s local-likelihood approach. Our method has a smaller integrated MSE, easily fixes the boundary bias, and requires far less computing time than the likelihood-based method.

Comments

This is a manuscript of an article published as Kim, Eunice J., and Zhengyuan Zhu. "Variance function estimation of a one-dimensional nonstationary process." Journal of the Korean Statistical Society (2019). doi: 10.1016/j.jkss.2019.01.001. Posted with permission.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

The Korean Statistical Society

Language

en

File Format

application/pdf

Available for download on Saturday, January 25, 2020

Published Version

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