Semiparametric regression models with additive nonparametric components and high dimensional parametric components

DOI10.1016/j.csda.2011.12.007zbMath1243.62053OpenAlexW2005928212MaRDI QIDQ435000

Pang Du, Guang Cheng, Hua Liang

Publication date: 16 July 2012

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

Full work available at URL: https://doi.org/10.1016/j.csda.2011.12.007

zbMATH Keywords

model selectionadditive modelssparsitySCADbackfittingpartial smoothing splines

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12)

Related Items

The exponentiated power exponential semiparametric regression model ⋮ Variable selection in functional additive regression models ⋮ Two-stage Walsh-average-based robust estimation and variable selection for partially linear additive spatial autoregressive models ⋮ Using thresholding difference-based estimators for variable selection in partial linear models ⋮ Nonconvex penalized ridge estimations for partially linear additive models in ultrahigh dimension ⋮ Additive monotone regression in high and lower dimensions ⋮ Profile statistical inference for partially linear additive models with a diverging number of parameters ⋮ Variable selection in high-dimensional partially linear additive models for composite quantile regression ⋮ Estimation in the partially nonlinear model by continuous optimization

Uses Software

• gss
• hgam

Cites Work

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