Asymptotic normality of DHD estimators in a partially linear model

DOI10.1007/s00362-015-0666-2zbMath1349.62132OpenAlexW2069969984MaRDI QIDQ345349

Xiong Pan, Yu Zhang, Hong Chang Hu

Publication date: 1 December 2016

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-015-0666-2

zbMATH Keywords

asymptotic normalityHuber-Dutter estimatordifference-based methodpartially linear regression modelweak convergence rate

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05)

Related Items

A difference-based approach in the partially linear model with dependent errors ⋮ Optimal difference-based estimation for partially linear models ⋮ Strong consistency of estimators in a partially linear model with asymptotically almost negatively associated errors ⋮ Consistency for wavelet estimator in nonparametric regression model with extended negatively dependent samples ⋮ Asymptotic normality and mean consistency of LS estimators in the errors-in-variables model with dependent errors ⋮ Difference-based M-estimator of generalized semiparametric model with NSD errors

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