Sequential feature screening for generalized linear models with sparse ultra-high dimensional data
From MaRDI portal
Publication:2200110
DOI10.1007/s11424-020-8273-2zbMath1448.62116OpenAlexW3022474813MaRDI QIDQ2200110
Hang Wang, Jiajia Zhang, Jun-ying Zhang, Ri-quan Zhang
Publication date: 15 September 2020
Published in: Journal of Systems Science and Complexity (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11424-020-8273-2
variable selectiongeneralized linear modelvariable screeningsequential iterationextended Bayesian information criteria (extended BIC)sequential Lasso
Ridge regression; shrinkage estimators (Lasso) (62J07) Generalized linear models (logistic models) (62J12) Statistical aspects of information-theoretic topics (62B10) Sequential estimation (62L12)
Cites Work
- Unnamed Item
- Unnamed Item
- Sure independence screening in generalized linear models with NP-dimensionality
- Nearly unbiased variable selection under minimax concave penalty
- The Adaptive Lasso and Its Oracle Properties
- Least angle regression. (With discussion)
- Extended BIC for small-n-large-P sparse GLM
- Extended Bayesian information criteria for model selection with large model spaces
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- Sequential Lasso Cum EBIC for Feature Selection With Ultra-High Dimensional Feature Space
- Shrinkage Estimation of the Varying Coefficient Model
- Empirical Bayes Estimates for Large-Scale Prediction Problems
- Nonconcave Penalized Likelihood With NP-Dimensionality