Sparse linear mixed model selection via streamlined variational Bayes
From MaRDI portal
Publication:2084474
DOI10.1214/22-EJS2063OpenAlexW3205586694MaRDI QIDQ2084474
Emanuele Degani, Luca Maestrini, Dorota Toczydłowska, Matthew P. Wand
Publication date: 18 October 2022
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2110.07048
longitudinal data analysismultilevel modelsmean field variational Bayesfixed effects selectionglobal-local shrinkage priors
Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Bayesian inference (62F15)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The Adaptive Lasso and Its Oracle Properties
- Mean field variational Bayes for continuous sparse signal shrinkage: pitfalls and remedies
- Sparse variational analysis of linear mixed models for large data sets
- Asymptotic Bayes-optimality under sparsity of some multiple testing procedures
- Bayesian adaptive Lasso
- Bayesian group Lasso for nonparametric varying-coefficient models with application to functional genome-wide association studies
- Variable selection for generalized linear mixed models by \(L_1\)-penalized estimation
- Microarrays, empirical Bayes and the two-groups model
- Simple marginally noninformative prior distributions for covariance matrices
- RcppArmadillo: accelerating R with high-performance C++ linear algebra
- Variable selection via penalized credible regions with Dirichlet-Laplace global-local shrinkage priors
- Variable selection using shrinkage priors
- The horseshoe+ estimator of ultra-sparse signals
- Variational message passing for elaborate response regression models
- Doubly regularized estimation and selection in linear mixed-effects models for high-dimensional longitudinal data
- Optimal predictive model selection.
- Variable selection in linear mixed effects models
- Bayesian variable selection for mixed effects model with shrinkage prior
- Econometric analysis of panel data
- Lasso meets horseshoe: a survey
- General design Bayesian generalized linear mixed models
- Spike and slab variable selection: frequentist and Bayesian strategies
- A variational Bayes approach to variable selection
- Empirical Bayes selection of wavelet thresholds
- Scalable variational inference for Bayesian variable selection in regression, and its accuracy in genetic association studies
- Mean field variational Bayes for elaborate distributions
- Inference with normal-gamma prior distributions in regression problems
- BAYESIAN HYPER-LASSOS WITH NON-CONVEX PENALIZATION
- Using Infer.NET for Statistical Analyses
- Estimation for High-Dimensional Linear Mixed-Effects Models Using ℓ1-Penalization
- Small Area Estimation
- Variational Bayesian Inference for Parametric and Nonparametric Regression With Missing Data
- Explaining Variational Approximations
- Streamlined mean field variational Bayes for longitudinal and multilevel data analysis
- Random Effects Selection in Linear Mixed Models
- The horseshoe estimator for sparse signals
- The Bayesian Lasso
- Bayesian Variable Selection in Linear Regression
- Semiparametric Regression
- A Statistical View of Some Chemometrics Regression Tools
- Consistent High-Dimensional Bayesian Variable Selection via Penalized Credible Regions
- Generalized double Pareto shrinkage
- Bayesian nonparametric centered random effects models with variable selection
- STREAMLINED SOLUTIONS TO MULTILEVEL SPARSE MATRIX PROBLEMS
- Streamlined variational inference for higher level group-specific curve models
- Bayesian adaptive lasso with variational Bayes for variable selection in high-dimensional generalized linear mixed models
- Regularization and Variable Selection Via the Elastic Net
- Decoupling Shrinkage and Selection in Bayesian Linear Models: A Posterior Summary Perspective
- Dirichlet–Laplace Priors for Optimal Shrinkage
- Fixed and Random Effects Selection in Linear and Logistic Models
- The Geometry of Information Retrieval
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- Linear mixed models for longitudinal data
- A review of Bayesian variable selection methods: what, how and which
- Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
- The Inverse G‐Wishart distribution and variational message passing
