L1-estimation for varying coefficient models

DOI10.1080/02331880500310165zbMath1089.62048OpenAlexW2046169060MaRDI QIDQ5475300

Qingguo Tang, Jinde Wang

Publication date: 16 June 2006

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331880500310165

zbMATH Keywords

asymptotic normalityvarying coefficient modelleast absolute deviation estimationabsolute cross validation (ACV)ACV bandwidth selection

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

Related Items (16)

Adaptive jump-preserving estimates in varying-coefficient models ⋮ Asymptotic Normality ofM-Estimators for Varying Coefficient Models with Longitudinal Data ⋮ Componentwise B-spline estimation for varying coefficient models with longitudinal data ⋮ Least absolute deviation estimate for functional coefficient partially linear regression models ⋮ Varying Coefficient Regression Models: A Review and New Developments ⋮ Wavelet-L₁-estimation for non parametric location-scale models under a general dependence framework ⋮ Reducing component estimation for varying coefficient models ⋮ L₁-estimation for spatial nonparametric regression ⋮ Reducing component estimation for varying coefficient models with longitudinal data ⋮ Asymptotic normality of M-estimators in a semiparametric model with longitudinal data ⋮ Analysis of longitudinal data with semiparametric varying-coefficient mean-covariance models ⋮ \(L_1\)-estimation for covariate-adjusted regression ⋮ Asymptotics for \(L_1\)-wavelet method for nonparametric regression ⋮ Estimation of semi-varying coefficient models for longitudinal data with irregular error structure ⋮ B-spline estimation for varying coefficient regression with spatial data ⋮ Local Linear Estimation for Spatiotemporal Models Based on Least Absolute Deviation

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