Kernel Estimators for Additive Models with Dependent Observations from Random Fields

DOI10.1080/03610926.2011.579373zbMath1347.62060OpenAlexW2053549364MaRDI QIDQ4921637

Jiexiang Li

Publication date: 13 May 2013

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

Full work available at URL: https://doi.org/10.1080/03610926.2011.579373

zbMATH Keywords

asymptotic normalityNadaraya-Watson estimatorrandom fieldadditive model

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Cites Work

• Kernel estimation for additive models under dependence
• Kernel density estimation on random fields
• Additive regression and other nonparametric models
• Local linear spatial regression
• Residual variance and residual pattern in nonlinear regression
• Robust kernel estimators for additive models with dependent observations

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