New \(M\)-estimators in semi-parametric regression with errors in variables

DOI10.1214/07-AIHP107zbMath1206.62068arXivmath/0511105MaRDI QIDQ731676

Cristina Butucea, Marie-Luce Taupin

Publication date: 8 October 2009

Published in: Annales de l'Institut Henri Poincaré. Probabilités et Statistiques (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0511105

zbMATH Keywords

consistencyasymptotic normalityrates of convergencedeconvolution kernel estimatorordinary smooth and super-smooth functionssemi-parametric nonlinear regression

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) General nonlinear regression (62J02)

Related Items (5)

NONPARAMETRIC SIGNIFICANCE TESTING IN MEASUREMENT ERROR MODELS ⋮ Comment on identification and estimation of nonlinear models using two samples with nonclassical measurement errors ⋮ SPECIFICATION TESTING FOR ERRORS-IN-VARIABLES MODELS ⋮ Estimation of the hazard function in a semiparametric model with covariate measurement error ⋮ Measurement error models: from nonparametric methods to deep neural networks

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