Robust nonparametric kernel regression estimator

Ge Zhao, Yanyuan Ma

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

In robust nonparametric kernel regression context, we prescribe method to select trimming parameter and bandwidth. Through solving estimating equations, we control outlier effect through combining weighting and trimming. We show asymptotic consistency, establish bias, variance properties and derive asymptotics.

Original languageEnglish (US)
Pages (from-to)72-79
Number of pages8
JournalStatistics and Probability Letters
Volume116
DOIs
StatePublished - Sep 1 2016

Fingerprint

Kernel Regression
Trimming
Regression Estimator
Kernel Estimator
Nonparametric Regression
Estimating Equation
Outlier
Weighting
Bandwidth
Kernel regression
Estimator
Context
Outliers

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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title = "Robust nonparametric kernel regression estimator",
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Robust nonparametric kernel regression estimator. / Zhao, Ge; Ma, Yanyuan.

In: Statistics and Probability Letters, Vol. 116, 01.09.2016, p. 72-79.

Research output: Contribution to journalArticle

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AU - Ma, Yanyuan

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