Incomplete graphical model inference via latent tree aggregation

DOI10.1177/1471082X18786289WikidataQ129302315 ScholiaQ129302315MaRDI QIDQ5142256

Christophe Ambroise, Geneviève Robin, Stephane Robin

Publication date: 30 December 2020

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1705.09464

zbMATH Keywords

EM algorithmmodel selectionlatent variablesGaussian graphical model

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• R
• glasso

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• On the shortest spanning subtree of a graph and the traveling salesman problem
• Sparse inverse covariance estimation with the graphical lasso
• Latent variable graphical model selection via convex optimization
• Estimating the dimension of a model
• A classification EM algorithm for clustering and two stochastic versions
• Knowledge representation and inference in similarity networks and Bayesian multinets
• 10.1162/153244301753344605
• A Combinatorial Proof of the All Minors Matrix Tree Theorem
• The correlation space of Gaussian latent tree models and model selection without fitting
• Learning Latent Tree Graphical Models
• Approximating discrete probability distributions with dependence trees
• Discussion: Latent variable graphical model selection via convex optimization
• Discussion: Latent variable graphical model selection via convex optimization

This page was built for publication: Incomplete graphical model inference via latent tree aggregation