Are efficient estimators in single-indexed models really efficient? A computational discussion

DOI10.1007/S001800200119zbMath1037.62033OpenAlexW2912506281MaRDI QIDQ1424611

Marian Hristache

Publication date: 16 March 2004

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s001800200119

zbMATH Keywords

asymptotic efficiencyM-estimatorsemiparametric approachNaradaya-Watson kernel estimator

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Numerical smoothing, curve fitting (65D10) General nonlinear regression (62J02) Monte Carlo methods (65C05)

Cites Work

• How sensitive are average derivatives?
• Semiparametric least squares (SLS) and weighted SLS estimation of single-index models
• Semiparametric \(M\)-estimators in single-index models
• Optimal smoothing in single-index models
• On semiparametric \(M\)-estimation in single-index regression
• Efficiency of Weighted Average Derivative Estimators and Index Models
• Investigating Smooth Multiple Regression by the Method of Average Derivatives
• Consistent Estimation of Scaled Coefficients
• Bandwidth Choice for Average Derivative Estimation
• Semiparametric Estimation of Index Coefficients
• The Normal Approximation for Semiparametric Averaged Derivatives
• An Efficient Semiparametric Estimator for Binary Response Models

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