Variable selection and subgroup analysis for high-dimensional censored data
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Publication:6620580
DOI10.1080/24754269.2024.2327113MaRDI QIDQ6620580
Jiangli Wang, Weiping Zhang, Author name not available (Why is that?)
Publication date: 17 October 2024
Published in: Statistical Theory and Related Fields (Search for Journal in Brave)
Cites Work
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Nearly unbiased variable selection under minimax concave penalty
- Estimation of Relationships for Limited Dependent Variables
- The Adaptive Lasso and Its Oracle Properties
- Censored linear model in high dimensions. Penalised linear regression on high-dimensional data with left-censored response variable
- Regularization for Cox's proportional hazards model with NP-dimensionality
- Tobit models: A survey
- Least absolute deviations estimation for the censored regression model
- On Lasso for censored data
- Bayesian Elastic Net Tobit Quantile Regression
- Shrinkage Tuning Parameter Selection with a Diverging number of Parameters
- A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)
- Note on the Uniqueness of the Maximum Likelihood Estimator for the Tobit Model
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Regression Analysis when the Dependent Variable Is Truncated Normal
- A growth mixture Tobit model: application to AIDS studies
- Inference for Subgroup Analysis With a Structured Logistic-Normal Mixture Model
- Tuning parameter selectors for the smoothly clipped absolute deviation method
- Simultaneous Regression Shrinkage, Variable Selection, and Supervised Clustering of Predictors with OSCAR
- LAD-Lasso variable selection for doubly censored median regression models
- Tuning Parameter Selection in High Dimensional Penalized Likelihood
- Convergence of a block coordinate descent method for nondifferentiable minimization
- High-Dimensional Censored Regression via the Penalized Tobit Likelihood
- Exploration of heterogeneous treatment effects via concave fusion
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