Estimation and variable selection for generalised partially linear single-index models

DOI10.1080/10485252.2013.841156zbMath1359.62127OpenAlexW2177214397MaRDI QIDQ5419460

Peng Lai, Ye Tian, Heng Lian

Publication date: 6 June 2014

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2013.841156

zbMATH Keywords

variable selectionquasi-likelihoodoracle propertySCAD penalty

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Generalized linear models (logistic models) (62J12) General nonlinear regression (62J02) Statistical ranking and selection procedures (62F07)

Related Items (1)

Variable selection for the partial linear single-index model

Cites Work

• Estimation and testing for partially linear single-index models
• The Adaptive Lasso and Its Oracle Properties
• The EFM approach for single-index models
• Empirical likelihood inference in partially linear single-index models for longitudinal data
• Nonconcave penalized inverse regression in single-index models with high dimensional predic\-tors
• Semiparametric least squares (SLS) and weighted SLS estimation of single-index models
• Optimal smoothing in single-index models
• Variable selection in semiparametric regression modeling
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Penalized Spline Estimation for Partially Linear Single-Index Models
• On extended partially linear single-index models
• Identifiability of single-index models and additive-index models

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