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Geometry of maximum likelihood estimation in Gaussian graphical models

ANNALS OF STATISTICS, no. 1 (2012): 238-261

Cited: 54|Views24

Abstract

We study maximum likelihood estimation in Gaussian graphical models from a geometric point of view. An algebraic elimination criterion allows us to find exact lower bounds on the number of observations needed to ensure that the maximum likelihood estimator (MLE) exists with probability one. This is applied to bipartite graphs, grids and c...More

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