The Annals of Statistics

Comparison of Two Bandwidth Selectors with Dependent Errors

C.-K. Chu and J. S. Marron

Full-text: Open access

Abstract

For nonparametric regression, in the case of dependent observations, cross-validation is known to be severely affected by dependence. This effect is precisely quantified through a limiting distribution for the cross-validated bandwidth. The performance of two methods, the "leave-$(2l + 1)$-out" version of cross-validation and partitioned cross-validation, which adjust for the effect of dependence on bandwidth selection is investigated. The bandwidths produced by these two methods are analyzed by further limiting distributions which reveal significantly different characteristics. Simulations demonstrate that the asymptotic effects hold for reasonable sample sizes.

Article information

Source
Ann. Statist., Volume 19, Number 4 (1991), 1906-1918.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176348377

Digital Object Identifier
doi:10.1214/aos/1176348377

Mathematical Reviews number (MathSciNet)
MR1135155

Zentralblatt MATH identifier
0738.62042

JSTOR
links.jstor.org

Subjects
Primary: 62G05: Estimation
Secondary: 62G20: Asymptotic properties

Keywords
Cross-validation partitioned cross-validation autoregressive moving average process bandwidth selector nonparametric regression

Citation

Chu, C.-K.; Marron, J. S. Comparison of Two Bandwidth Selectors with Dependent Errors. Ann. Statist. 19 (1991), no. 4, 1906--1918. doi:10.1214/aos/1176348377. https://projecteuclid.org/euclid.aos/1176348377


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