Statistical Science

On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression

Wenlin Dai, Tiejun Tong, and Lixing Zhu

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Abstract

Difference-based methods do not require estimating the mean function in nonparametric regression and are therefore popular in practice. In this paper, we propose a unified framework for variance estimation that combines the linear regression method with the higher-order difference estimators systematically. The unified framework has greatly enriched the existing literature on variance estimation that includes most existing estimators as special cases. More importantly, the unified framework has also provided a smart way to solve the challenging difference sequence selection problem that remains a long-standing controversial issue in nonparametric regression for several decades. Using both theory and simulations, we recommend to use the ordinary difference sequence in the unified framework, no matter if the sample size is small or if the signal-to-noise ratio is large. Finally, to cater for the demands of the application, we have developed a unified R package, named VarED, that integrates the existing difference-based estimators and the unified estimators in nonparametric regression and have made it freely available in the R statistical program http://cran.r-project.org/web/packages/.

Article information

Source
Statist. Sci., Volume 32, Number 3 (2017), 455-468.

Dates
First available in Project Euclid: 1 September 2017

Permanent link to this document
https://projecteuclid.org/euclid.ss/1504253126

Digital Object Identifier
doi:10.1214/17-STS613

Mathematical Reviews number (MathSciNet)
MR3696005

Zentralblatt MATH identifier
06870255

Keywords
Difference-based estimator nonparametric regression optimal difference sequence ordinary difference sequence residual variance

Citation

Dai, Wenlin; Tong, Tiejun; Zhu, Lixing. On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression. Statist. Sci. 32 (2017), no. 3, 455--468. doi:10.1214/17-STS613. https://projecteuclid.org/euclid.ss/1504253126


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Supplemental materials

  • Supplement to “On the Choice of Difference Sequence in a Unified Framework for Variance Estimation in Nonparametric Regression.”.