Joint Estimation of the Two-Level Gaussian Graphical Models Across Multiple Classes
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Publication:5066004
DOI10.1080/10618600.2019.1694522OpenAlexW2990805628MaRDI QIDQ5066004
Lulu Cheng, Inyoung Kim, Zhilei Qiao, Liang Shan
Publication date: 28 March 2022
Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10618600.2019.1694522
Gaussian graphical modelprecision matrix estimationjoint estimationtwo-level networkheterogeneous classes
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Cites Work
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- Sparse inverse covariance estimation with the graphical lasso
- The Adaptive Lasso and Its Oracle Properties
- Group variable selection via a hierarchical lasso and its oracle property
- Covariance regularization by thresholding
- Joint estimation of multiple Gaussian graphical models across unbalanced classes
- Sparse permutation invariant covariance estimation
- Network exploration via the adaptive LASSO and SCAD penalties
- Multilevel Gaussian graphical model for multilevel networks
- High-dimensional graphs and variable selection with the Lasso
- Emergence of Scaling in Random Networks
- Joint estimation of multiple graphical models
- Extended Bayesian information criteria for model selection with large model spaces
- Model selection and estimation in the Gaussian graphical model
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Sparse Estimation of Conditional Graphical Models With Application to Gene Networks
- Structural Pursuit Over Multiple Undirected Graphs
- The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
- A hybrid omnibus test for generalized semiparametric single‐index models with high‐dimensional covariate sets
- Accurate Ranking of Differentially Expressed Genes by a Distribution-Free Shrinkage Approach
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