Forward selection and estimation in high dimensional single index models

DOI10.1016/J.STAMET.2016.09.002zbMath1487.62036OpenAlexW2525407547WikidataQ57429414 ScholiaQ57429414MaRDI QIDQ670181

Subhashis Ghosal, Shikai Luo

Publication date: 18 March 2019

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2016.09.002

zbMATH Keywords

penalizationvariable selectionsparsityhigh dimensionforward selectionsingle index model

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items (5)

Unnamed Item ⋮ Variable selection for single-index varying-coefficients models with applications to synergistic \(\mathrm{G} \times \mathrm{E}\) interactions ⋮ Local Walsh-average-based estimation and variable selection for single-index models ⋮ High dimensional single-index Bayesian modeling of brain atrophy ⋮ Nonparametric estimation of single-index models in scale-space

Uses Software

• glmnet

Cites Work

• Unnamed Item
• Unnamed Item
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• A note on shrinkage sliced inverse regression
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• Sliced Inverse Regression with Regularizations

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