Laplace error penalty-based M-type model detection for a class of high dimensional semiparametric models

DOI10.1016/j.cam.2018.08.020zbMath1407.62137OpenAlexW2888738034MaRDI QIDQ1631432

Ling Jian, Yunquan Song, Xiaoyu Ma, Shi Hua Luo

Publication date: 6 December 2018

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2018.08.020

zbMATH Keywords

robustnessvariable selectionhigh-dimensional modelsM-type estimatorbasis approximationdifference convex algorithmLaplace error penalty

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric robustness (62G35)

Related Items (1)

Robust check loss-based inference of semiparametric models and its application in environmental data

Uses Software

• SemiPar

Cites Work

• Unnamed Item
• The Adaptive Lasso and Its Oracle Properties
• Variable selection for single-index varying-coefficient model
• Empirical likelihood for single-index varying-coefficient models
• Statistical inference for a single-index varying-coefficient model
• Variable selection for semiparametric varying coefficient partially linear errors-in-variables models
• Model detection and estimation for single-index varying coefficient model
• Model structure selection in single-index-coefficient regression models
• Adaptive semi-varying coefficient model selection
• Laplace Error Penalty-based Variable Selection in High Dimension
• Inference for Nonparametric Parts in Single-Index Varying-Coefficient Model
• Semiparametric Regression
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• On Single-Index Coefficient Regression Models
• Semiparametric Regression for the Applied Econometrician
• Adaptive Varying-Coefficient Linear Models
• A practical guide to splines.

This page was built for publication: Laplace error penalty-based M-type model detection for a class of high dimensional semiparametric models