A partial graphical model with a structural prior on the direct links between predictors and responses

DOI10.1051/ps/2021010zbMath1469.62282arXiv2003.11869OpenAlexW3168248413MaRDI QIDQ5000397

Pascal Jézéquel, Eunice Okome Obiang, Frédéric Proïa

Publication date: 13 July 2021

Published in: ESAIM: Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2003.11869

zbMATH Keywords

convex optimizationsparsityhigh-dimensional linear regressionpartial graphical modelstructural penalization

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Parametric inference under constraints (62F30) Probabilistic graphical models (62H22)

Related Items (1)

A Bayesian approach for partial Gaussian graphical models with sparsity

Uses Software

• fda (R)
• bayesm
• glasso

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A sparse conditional Gaussian graphical model for analysis of genetical genomics data
• Sparse inverse covariance estimation with the graphical lasso
• Simultaneous multiple response regression and inverse covariance matrix estimation via penalized Gaussian maximum likelihood
• The structured elastic net for quantile regression and support vector classification
• Feature selection guided by structural information
• A simple proof of the restricted isometry property for random matrices
• High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
• Network exploration via the adaptive LASSO and SCAD penalties
• Structured regularization for conditional Gaussian graphical models
• Functional data analysis.
• High-dimensional graphs and variable selection with the Lasso
• Partial Gaussian Graphical Model Estimation
• A Constrainedℓ₁Minimization Approach to Sparse Precision Matrix Estimation
• Bayesian Statistics and Marketing
• Model selection and estimation in the Gaussian graphical model
• Smooth Optimization Approach for Sparse Covariance Selection
• Parameter Estimation For Multivariate Generalized Gaussian Distributions
• Partial Correlation Estimation by Joint Sparse Regression Models
• Covariate-adjusted precision matrix estimation with an application in genetical genomics

This page was built for publication: A partial graphical model with a structural prior on the direct links between predictors and responses