GEOMETRY OF MAXIMUM LIKELIHOOD ESTIMATION IN GAUSSIAN GRAPHICAL MODELS BY CAROLINE UHLER Institute of Science and Technology Austria

@inproceedings{Uhler2012GEOMETRYOM,
  title={GEOMETRY OF MAXIMUM LIKELIHOOD ESTIMATION IN GAUSSIAN GRAPHICAL MODELS BY CAROLINE UHLER Institute of Science and Technology Austria},
  author={Caroline Uhler},
  year={2012}
}
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 colored graphs. We also study the ML degree, and we present the first instance of a graph for which the MLE exists with probability one, even when the number of… CONTINUE READING
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