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Document type:
Zeitungsartikel 
Author(s):
Drton, M. and Richardson, T.S. 
Title:
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models 
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:
Pages contribution:
893-914 
Language:
en 
Publisher:
Microtome Publishing 
Publisher address:
Brookline, MA 
Print-ISSN:
1532-4435 
E-ISSN:
1533-7928 
Status:
Verlagsversion / published 
Date of publication:
01.05.2008 
Format:
Text