Design of kernel M-smoothers for spatial data

DOI10.1016/J.STAMET.2007.08.003zbMath1248.62047OpenAlexW2009541576MaRDI QIDQ713833

Carlo Grillenzoni

Publication date: 19 October 2012

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

Full work available at URL: https://doi.org/10.1016/j.stamet.2007.08.003

zbMATH Keywords

robust estimationparametric identifiabilitybandwidths selectioniterative smoothersjump-preserving

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Estimation in multivariate analysis (62H12) Nonparametric robustness (62G35) Nonparametric estimation (62G05)

Uses Software

• car
• KernSmooth
• robustbase
• CrimeStat

Cites Work

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• Adaptive \(M\)-estimation in nonparametric regression
• Robust plug-in bandwidth estimators in nonparametric regression
• Local polynomial \(M\)-smoothers in nonparametric regression
• Cross-validation in nonparametric regression with outliers
• On consistency of redescending M-kernel smoothers
• Bandwidth selection in robust smoothing
• Edge-Preserving Smoothers for Image Processing
• The L 1 Method for Robust Nonparametric Regression
• Recursive Generalized M-Estimators of System Parameters
• Automatic bandwidth selection for modified m-smoother^∗
• M-Smoother with local Linear Fit
• Robust Statistics
• Smoothing parameter selection methods for nonparametric regression with spatially correlated errors
• Robust Statistics

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