On the application of Gaussian graphical models to paired data problems
DOI10.1007/S11222-024-10513-6MaRDI QIDQ6657818
Alberto Roverato, Saverio Ranciati
Publication date: 7 January 2025
Published in: Statistics and Computing (Search for Journal in Brave)
symmetryconditional independencegraphical LassoADMM algorithmcoloured Gaussian graphical modelfused Lasso penalty
Computational methods for problems pertaining to statistics (62-08) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Probabilistic graphical models (62H22)
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Model selection in the space of Gaussian models invariant by symmetry
- Sparse inverse covariance estimation with the graphical lasso
- Lattices of graphical Gaussian models with symmetries
- The solution path of the generalized lasso
- Estimation of a covariance matrix under Stein's loss
- Pathwise coordinate optimization
- Model selection and estimation in the Gaussian graphical model
- Graphical Gaussian Models With Edge and Vertex Symmetries
- Sparsity and Smoothness Via the Fused Lasso
- The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
- Joint estimation of multiple dependent Gaussian graphical models with applications to mouse genomics
- Partial correlation graphical LASSO
- Joint Gaussian graphical model estimation: a survey
- Fused graphical lasso for brain networks with symmetries
This page was built for publication: On the application of Gaussian graphical models to paired data problems
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6657818)