Asymptotic normality for robust R-estimators of regression function

DOI10.1016/0378-3758(90)90037-UzbMath0687.62033OpenAlexW1990933611MaRDI QIDQ1263191

K. Appert

Publication date: 1990

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(90)90037-u

zbMATH Keywords

nonparametric regressionAsymptotic normalityR-estimatorsfixed design modelRobustness propertiesrandom design modelasymptotic variance parametersempirical conditional distributionsymmetric random noise

Mathematics Subject Classification ID

Nonparametric estimation (62G05) General nonlinear regression (62J02)

Cites Work

• Fitting a multiple regression function
• Robust regression function estimation
• Uniform consistency of a class of regression function estimators
• On the Glivenko-Cantelli theorem for weighted empiricals based on independent random variables
• Consistency properties of nearest neighbor density function estimators
• The strong uniform consistency of nearest neighbor density estimates
• Robust Estimation of a Location Parameter
• Robust Estimates of Location: Symmetry and Asymmetric Contamination
• Robust Estimates of Location: Survey and Advances
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