On asymptotic behavior of Nadaraya–Watson regression estimator

DOI10.1080/03610926.2014.948209zbMath1348.62139OpenAlexW2499220403MaRDI QIDQ2830788

Jiexiang Li

Publication date: 31 October 2016

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2014.948209

zbMATH Keywords

asymptotic normalityrandom fieldregression functionNadaraya-Watson regression estimator

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Nonparametric regression and quantile regression (62G08) Asymptotic distribution theory in statistics (62E20)

Cites Work

• Nonparametric function estimation for time series by local average estimators
• Nonparametric regression estimation under mixing conditions
• Strong uniform convergence rates in robust nonparametric time series analysis and prediction: Kernel regression estimation from dependent observations
• On the central limit theorem for stationary mixing random fields
• Spatial nonparametric regression estimation: Non-isotropic case
• Local linear spatial regression
• Nonparametric regression estimation for dependent functional data: asymptotic normality
• NONPARAMETRIC ESTIMATORS FOR TIME SERIES
• Recursive probability density estimation for weakly dependent stationary processes
• Conditions for linear processes to be strong-mixing
• Weak and strong uniform consistency of kernel regression estimates

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