Grouping Variable Selection by Weight Fused Elastic Net for Multi-Collinear Data

DOI10.1080/03610918.2011.579369zbMath1489.62200OpenAlexW2084167880MaRDI QIDQ2905731

Qingsong Xu, Guanghui Fu

Publication date: 28 August 2012

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2011.579369

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (2)

Multi-step adaptive elastic-net: reducing false positives in high-dimensional variable selection ⋮ Group Variable Selection with Oracle Property by Weight-Fused Adaptive Elastic Net Model for Strongly Correlated Data

Cites Work

• The Adaptive Lasso and Its Oracle Properties
• Shrinkage and model selection with correlated variables via weighted fusion
• Finding predictive gene groups from microarray data
• Least angle regression. (With discussion)
• On the adaptive elastic net with a diverging number of parameters
• Averaged gene expressions for regression
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Applied Linear Regression
• Sparsity and Smoothness Via the Fused Lasso
• Regularization and Variable Selection Via the Elastic Net
• Model Selection and Estimation in Regression with Grouped Variables
• Regression modeling strategies. With applications to linear models, logistic regression and survival analysis

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