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Title:

Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models

Document type:
Zeitungsartikel
Author(s):
Drton, Mathias; Richardson, Thomas S.
Abstract:
In graphical modelling, a bi-directed graph encodes marginal independences among random variables that are identified with the vertices of the graph. We show how to transform a bi-directed graph into a maximal ancestral graph that (i) represents the same independence structure as the original bi-directed graph, and (ii) minimizes the number of arrowheads among all ancestral graphs satisfying (i). Here the number of arrowheads of an ancestral graph is the number of directed edges plus twice the n...     »
Keywords:
Ancestral graph, covariance graph, graphical model, marginal independence, maxi-mum likelihood estimation, multivariate normal distribution
Dewey Decimal Classification:
510 Mathematik
Journal title:
Journal of Machine Learning Research
Year:
2008
Journal volume:
9
Year / month:
2008-05
Quarter:
2. Quartal
Month:
May
Pages contribution:
893-914
Language:
en
WWW:
Journal of Machine Learning Research
Publisher:
Microtome Publishing
Publisher address:
Brookline, MA
Print-ISSN:
1532-4435
E-ISSN:
1533-7928
Status:
Verlagsversion / published
Submitted:
01.10.2007
Date of publication:
01.05.2008
Format:
Text
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