A Bayesian approach for partial Gaussian graphical models with sparsity

DOI10.1214/22-ba1315arXiv2105.10888OpenAlexW3165126802MaRDI QIDQ6122031

Frédéric Proïa, Eunice Okome Obiang, Pascal Jézéquel

Publication date: 27 February 2024

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2105.10888

zbMATH Keywords

Gibbs samplersparsityspike-and-slabBayesian approachpartial correlationhigh-dimensional linear regressionpartial graphical model

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Bayesian inference (62F15) Probabilistic graphical models (62H22)

Cites Work

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• Sparse inverse covariance estimation with the graphical lasso
• Asymptotic normality and optimalities in estimation of large Gaussian graphical models
• Bayesian variable selection and estimation for group Lasso
• Optimal rates of convergence for sparse covariance matrix estimation
• Bayesian variable selection regression of multivariate responses for group data
• Sparse permutation invariant covariance estimation
• High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
• Consistent group selection with Bayesian high dimensional modeling
• Structured regularization for conditional Gaussian graphical models
• High-dimensional graphs and variable selection with the Lasso
• The Matsumoto\,-\,Yor property and the structure of the Wishart distribution
• Infinite mixtures of multivariate normal-inverse Gaussian distributions for clustering of skewed data
• Partial Gaussian Graphical Model Estimation
• A Constrainedℓ₁Minimization Approach to Sparse Precision Matrix Estimation
• Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure
• Model selection and estimation in the Gaussian graphical model
• The Bayesian Lasso
• Multivariate Bayesian Variable Selection and Prediction
• A partial graphical model with a structural prior on the direct links between predictors and responses
• Sparse Bayesian Additive Nonparametric Regression with Application to Health Effects of Pesticides Mixtures
• Spike-and-Slab Group Lassos for Grouped Regression and Sparse Generalized Additive Models
• Independent Component Analysis and Blind Signal Separation

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