Robust nonparametric kernel regression estimator

Ge Zhao; Yanyuan Ma

doi:10.1016/j.spl.2016.04.010

Robust nonparametric kernel regression estimator

Ge Zhao, Yanyuan Ma

Statistics

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

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 language	English (US)
Pages (from-to)	72-79
Number of pages	8
Journal	Statistics and Probability Letters
Volume	116
DOIs	https://doi.org/10.1016/j.spl.2016.04.010
State	Published - Sep 1 2016

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/j.spl.2016.04.010

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title = "Robust nonparametric kernel regression estimator",

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.",

author = "Ge Zhao and Yanyuan Ma",

year = "2016",

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doi = "10.1016/j.spl.2016.04.010",

language = "English (US)",

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AU - Ma, Yanyuan

PY - 2016/9/1

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JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

ER -

Robust nonparametric kernel regression estimator

Abstract

All Science Journal Classification (ASJC) codes

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