Distributed adaptive lasso penalized generalized linear models for big data
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Publication:6171897
DOI10.1080/03610918.2021.1888998OpenAlexW3133608021MaRDI QIDQ6171897
Publication date: 18 July 2023
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2021.1888998
parallel implementationquadratic approximationgeneralized linear modelsadaptive Lassoregularization pathdistributed big data
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Cites Work
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Nearly unbiased variable selection under minimax concave penalty
- The Adaptive Lasso and Its Oracle Properties
- Aggregated estimating equation estimation
- Least squares approximation with a diverging number of parameters
- Asymptotics for Lasso-type estimators.
- Least angle regression. (With discussion)
- On the asymptotics of constrained \(M\)-estimation
- Bridge estimation for generalized linear models with a diverging number of parameters
- On the adaptive elastic net with a diverging number of parameters
- Adaptive robust variable selection
- Adaptive Lasso estimators for ultrahigh dimensional generalized linear models
- Unified LASSO Estimation by Least Squares Approximation
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Sparse Estimation of Generalized Linear Models (GLM) via Approximated Information Criteria
- Adaptive Lasso for generalized linear models with a diverging number of parameters
- L 1-Regularization Path Algorithm for Generalized Linear Models
- ADMM for Penalized Quantile Regression in Big Data
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