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- W2949171909 abstract "An open problem in graphical Gaussian models is to determine the smallest number of observations needed to guarantee the existence of the maximum likelihood estimator of the covariance matrix with probability one. In this paper we formalize a closely related problem in which the existence of the maximum likelihood estimator is guaranteed for all generic observations. We call the number determined by this problem the Gaussian rank of the graph representing the model. We prove that the Gaussian rank is strictly between the subgraph connectivity number and the graph degeneracy number. These bounds are in general much sharper than the best bounds known in the literature and furthermore computable in polynomial time." @default.
- W2949171909 created "2019-06-27" @default.
- W2949171909 creator A5076640906 @default.
- W2949171909 date "2014-06-18" @default.
- W2949171909 modified "2023-09-27" @default.
- W2949171909 title "Sharper lower and upper bounds for the gaussian rank of a graph" @default.
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- W2949171909 hasPublicationYear "2014" @default.
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