\(\ell_{2,0}\)-norm based selection and estimation for multivariate generalized linear models

DOI10.1016/j.jmva.2021.104782zbMath1476.62106OpenAlexW3177249909MaRDI QIDQ2048127

Yanyan Li

Publication date: 5 August 2021

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2021.104782

zbMATH Keywords

multivariate generalized linear models\(\ell_{2,0}\)-norm

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Generalized linear models (logistic models) (62J12)

Related Items

Low-rank matrix estimation via nonconvex optimization methods in multi-response errors-in-variables regression

Uses Software

• Fahrmeir
• glm

Cites Work

• Nearly unbiased variable selection under minimax concave penalty
• The Adaptive Lasso and Its Oracle Properties
• On constrained and regularized high-dimensional regression
• Model determination and estimation for the growth curve model via group SCAD penalty
• Consistent group selection in high-dimensional linear regression
• Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer
• Convex multi-task feature learning
• On the oracle property of a generalized adaptive elastic-net for multivariate linear regression with a diverging number of parameters
• Probability inequalities for likelihood ratios and convergence rates of sieve MLEs
• Subspace quadratic regularization method for group sparse multinomial logistic regression
• Support union recovery in high-dimensional multivariate regression
• A rich family of generalized Poisson regression models with applications
• High-dimensional graphs and variable selection with the Lasso
• Convergence and sparsity of Lasso and group Lasso in high-dimensional generalized linear models
• Variable selection and estimation in generalized linear models with the seamless ${\it L}_{{\rm 0}}$ penalty
• Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• First-Order Methods in Optimization
• Likelihood-Based Selection and Sharp Parameter Estimation
• Variable selection for multivariate generalized linear models
• Minimax Rates of Estimation for High-Dimensional Linear Regression Over $\ell_q$-Balls
• Visual Classification With Multitask Joint Sparse Representation
• Smoothly Clipped Absolute Deviation on High Dimensions
• Multivariate statistical modelling based on generalized linear models.
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item