Variable selection and semiparametric efficient estimation for the heteroscedastic partially linear single-index model

DOI10.1016/j.csda.2013.09.012zbMath1471.62105OpenAlexW1971954772MaRDI QIDQ1615234

Peng Lai, Xiao-Hua Andrew Zhou, Qi Hua Wang

Publication date: 2 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2013.09.012

zbMATH Keywords

heteroscedasticityestimating equationsvariable selectionoracle propertyefficient score function

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08)

Related Items

Smooth-threshold estimating equations for varying coefficient partially nonlinear models based on orthogonality-projection method, Efficient estimation for the heteroscedastic single-index varying coefficient models, Efficiency for heteroscedastic regression with responses missing at random, Estimation and variable selection for a class of quantile regression models with multiple index, Empirical likelihood in single-index quantile regression with high dimensional and missing observations, Variable selection for nonparametric quantile regression via measurement error model, Efficient estimation for marginal generalized partially linear single-index models with longitudinal data, Variable selection for the partial linear single-index model, Model identification and selection for single-index varying-coefficient models

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