Graphical Model Selection for Gaussian Conditional Random Fields in the Presence of Latent Variables

DOI10.1080/01621459.2018.1434531zbMath1420.62244arXiv1512.06412OpenAlexW2785368249WikidataQ57202042 ScholiaQ57202042MaRDI QIDQ5231501

Gilean McVean, Benjamin Frot, Luke Jostins

Publication date: 27 August 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1512.06412

zbMATH Keywords

geneticsmodel selectionmultivariate analysismetabolitesALSPAClow-rank plus sparseconditional Markov random field

Mathematics Subject Classification ID

Multivariate analysis (62H99) Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (2)

Bayesian Estimation of Gaussian Conditional Random Fields ⋮ Robust Causal Structure Learning with Some Hidden Variables

Uses Software

• SDPT3
• glasso

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• A sparse conditional Gaussian graphical model for analysis of genetical genomics data
• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Solving semidefinite-quadratic-linear programs using SDPT3
• Sparse inverse covariance estimation with the graphical lasso
• Latent variable graphical model selection via convex optimization
• On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
• The convex geometry of linear inverse problems
• High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
• Robust principal component analysis?
• Solving Log-Determinant Optimization Problems by a Newton-CG Primal Proximal Point Algorithm
• Rank-Sparsity Incoherence for Matrix Decomposition
• The Split Bregman Method for L1-Regularized Problems
• Model selection and estimation in the Gaussian graphical model
• Stability Selection
• Semidefinite Programming
• Variable Selection with Error Control: Another Look at Stability Selection
• Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection

This page was built for publication: Graphical Model Selection for Gaussian Conditional Random Fields in the Presence of Latent Variables