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Titel:

Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models

Dokumenttyp:
Zeitungsartikel
Autor(en):
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...     »
Stichworte:
Ancestral graph, covariance graph, graphical model, marginal independence, maxi-mum likelihood estimation, multivariate normal distribution
Dewey Dezimalklassifikation:
510 Mathematik
Zeitschriftentitel:
Journal of Machine Learning Research
Jahr:
2008
Band / Volume:
9
Jahr / Monat:
2008-05
Quartal:
2. Quartal
Monat:
May
Seitenangaben Beitrag:
893-914
Sprache:
en
WWW:
Journal of Machine Learning Research
Verlag / Institution:
Microtome Publishing
Verlagsort:
Brookline, MA
Print-ISSN:
1532-4435
E-ISSN:
1533-7928
Status:
Verlagsversion / published
Eingereicht (bei Zeitschrift):
01.10.2007
Publikationsdatum:
01.05.2008
Format:
Text
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