Local Walsh-average regression for semiparametric varying-coefficient models

Suoping Shang, Changliang Zou and Zhaojun Wang

Statistics & Probability Letters, 2012, vol. 82, issue 10, 1815-1822

Abstract: This work is concerned with robust estimation in a semiparametric varying-coefficient partially linear model when the underlying error distribution deviates from a normal distribution. We develop a robust estimator by minimizing a locally Walsh-average-based loss function. We show theoretically that the proposed estimator is highly efficient across a wide spectrum of distributions. Its asymptotic relative efficiency with respect to the least-squares-based method is closely related to that of the signed-rank Wilcoxon test in comparison with the t-test. Both the theoretical and the numerical results demonstrate that the performance of the new approach is at least comparable to those of existing works.

Keywords: Asymptotic efficiency; Local linear regression; Robust nonparametric regression; Semiparametric composite quantile estimator; Walsh-average (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:82:y:2012:i:10:p:1815-1822

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DOI: 10.1016/j.spl.2012.05.028

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