Robust Signed-Rank Variable Selection in Linear Regression

DOI10.1007/978-3-319-39065-9_2zbMath1366.62144OpenAlexW2522897241MaRDI QIDQ5280257

Huybrechts F. Bindele, Asheber Abebe

Publication date: 20 July 2017

Published in: Robust Rank-Based and Nonparametric Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-39065-9_2

zbMATH Keywords

Gaussianlinear regressionoracle propertyadaptive Lassopenalized least squaresLAD regressionsigned-rank variable selectionWilcoxon estimation

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Ridge regression; shrinkage estimators (Lasso) (62J07) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Linear regression; mixed models (62J05)

Related Items (4)

Robust signed-rank estimation and variable selection for semi-parametric additive partial linear models ⋮ Double penalized semi-parametric signed-rank regression with adaptive LASSO ⋮ Generalized signed-rank estimation and selection for the functional linear model ⋮ Robust estimation and selection for single-index regression model

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• Rank-Based Estimates in the Linear Model with High Breakdown Point
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Regularization and Variable Selection Via the Elastic Net
• Robust Nonparametric Statistical Methods

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