Fast marginal likelihood estimation of penalties for group-adaptive elastic net
From MaRDI portal
Publication:108783
DOI10.1080/10618600.2022.2128809arXiv2101.03875OpenAlexW3120244609MaRDI QIDQ108783
Tim van de Brug, Mark A. Van De Wiel, Mirrelijn M. Van Nee
Publication date: 11 January 2021
Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2101.03875
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Improving the INLA approach for approximate Bayesian inference for latent Gaussian models
- IPF-LASSO: integrative \(L_1\)-penalized regression with penalty factors for prediction based on multi-omics data
- The Bayesian elastic net
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- On the behaviour of marginal and conditional AIC in linear mixed models
- The Group Lasso for Logistic Regression
- Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction
- Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models
- Fast Cross-validation for Multi-penalty High-dimensional Ridge Regression
- Estimation of variance components, heritability and the ridge penalty in high-dimensional generalized linear models
- Regularization and Variable Selection Via the Elastic Net
- A Multivariate Central Limit Theorem for Random Linear Vector Forms
- A selective review of group selection in high-dimensional models
This page was built for publication: Fast marginal likelihood estimation of penalties for group-adaptive elastic net
