Adaptive sparse group LASSO in quantile regression
From MaRDI portal
Publication:2051571
DOI10.1007/s11634-020-00413-8OpenAlexW3045809290MaRDI QIDQ2051571
Alvaro Mendez-Civieta, M. Carmen Aguilera-Morillo, Rosa Elvira Lillo
Publication date: 24 November 2021
Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/10251/176337
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The Adaptive Lasso and Its Oracle Properties
- Group variable selection via a hierarchical lasso and its oracle property
- Nonconcave penalized likelihood with a diverging number of parameters.
- On the asymptotic properties of the group lasso estimator for linear models
- Statistical consistency and asymptotic normality for high-dimensional robust \(M\)-estimators
- Asymptotic theory of the adaptive sparse group Lasso
- Adaptive fused LASSO in grouped quantile regression
- A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification
- Asymptotic properties of bridge estimators in sparse high-dimensional regression models
- Adaptive group Lasso selection in quantile models
- CVXPY: A Python-Embedded Modeling Language for Convex Optimization
- An Iterative Sparse-Group Lasso
- Regression Quantiles
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Sparse Partial Least Squares Regression for Simultaneous Dimension Reduction and Variable Selection
- Quantile Regression for Analyzing Heterogeneity in Ultra-High Dimension
- Sparse group variable selection based on quantile hierarchical Lasso
- Smoothly Clipped Absolute Deviation on High Dimensions
- Model Selection and Estimation in Regression with Grouped Variables
- Robust Statistics
- On the grouped selection and model complexity of the adaptive elastic net
This page was built for publication: Adaptive sparse group LASSO in quantile regression