Inequalities on partial correlations in Gaussian graphical models containing star shapes
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Publication:2830188
DOI10.1080/03610926.2014.953696zbMath1349.62239OpenAlexW2308658158MaRDI QIDQ2830188
Publication date: 9 November 2016
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2014.953696
Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05)
Cites Work
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- Sparse estimation of a covariance matrix
- Sparse inverse covariance estimation with the graphical lasso
- A theorem on inverses of tridiagonal matrices
- High-dimensional structure estimation in Ising models: local separation criterion
- Coordinate descent algorithm for covariance graphical Lasso
- Operator norm consistent estimation of large-dimensional sparse covariance matrices
- Efficient Gaussian graphical model determination under \(G\)-Wishart prior distributions
- High-dimensional graphs and variable selection with the Lasso
- Bayesian graphical Lasso models and efficient posterior computation
- Joint estimation of multiple graphical models
- Estimation of a covariance matrix with zeros
- Positive Definite Matrices and Sylvester's Criterion
- Hyper Inverse Wishart Distribution for Non-decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models
- Learning Gaussian Tree Models: Analysis of Error Exponents and Extremal Structures
- Sampling decomposable graphs using a Markov chain on junction trees
- Simulation of hyper-inverse Wishart distributions in graphical models
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