Bi-level variable selection via adaptive sparse group Lasso
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Publication:5220909
DOI10.1080/00949655.2014.938241zbMath1457.62208OpenAlexW2066604793MaRDI QIDQ5220909
Shuangge Ma, Shengwei Zhang, Kuangnan Fang, Xiao-Yan Wang, Jian-Ping Zhu
Publication date: 27 March 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2014.938241
Computational methods for problems pertaining to statistics (62-08) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)
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Cites Work
- Unnamed Item
- Penalized methods for bi-level variable selection
- The Adaptive Lasso and Its Oracle Properties
- Consistent group selection in high-dimensional linear regression
- A note on adaptive group Lasso
- Heuristics of instability and stabilization in model selection
- High-dimensional variable screening and bias in subsequent inference, with an empirical comparison
- On the adaptive elastic net with a diverging number of parameters
- A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)
- The Group Lasso for Logistic Regression
- A group bridge approach for variable selection
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- A Statistical View of Some Chemometrics Regression Tools
- Regularization and Variable Selection Via the Elastic Net
- Model Selection and Estimation in Regression with Grouped Variables
- Convergence of a block coordinate descent method for nondifferentiable minimization
- A selective review of group selection in high-dimensional models
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