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Composite likelihood estimation of sparse Gaussian graphical models with symmetry
Variable selection model selection penalized estimation Gaussian graphical model concentration matrix partial correlation matrix
2012/9/17
In this article, we discuss the composite likelihood estimation of sparse Gaussian graph-ical models. When there are symmetry constraints on the concentration matrix or partial correlation matrix, the...
Inferring sparse Gaussian graphical models with latent structure
Gaussian graphical model Mixture model ℓ 1-penalization Model selection Variational inference EM algorithm
2009/9/16
Our concern is selecting the concentration matrix's nonzero coefficients for a sparse Gaussian graphical model in a high-dimensional setting. This corresponds to estimating the graph of conditional de...