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Computational Algebra and Maximum Likelihood Estimation in Gaussian graphical Models

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Dr. Caroline Uhler (IST Austria, Klosterneuburg), 10 May 2012, 2:30 pm, RISC seminar room
When May 10, 2012
from 02:30 PM to 03:30 PM
Where RISC seminar room
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Computational Algebra and Maximum Likelihood Estimation in Gaussian graphical Models

We study maximum likelihood estimation in Gaussian graphical models from an algebraic point of view. In current applications of statistics, we are often faced with problems involving a large number of random variables, but only a small number of observations. An algebraic elimination criterion allows us to find exact lower bounds on the number of observations needed to ensure that the maximum likelihood estimator exists with probability one. The use of Groebner bases is essential for the elimination criterion and allows us to solve this statistical problem for various graphs.