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Title:

A SINful approach to Gaussian graphical model selection

Document type:
Zeitschriftenaufsatz
Author(s):
Drton, Mathias; Perlman, Michael D.
Abstract:
Multivariate Gaussian graphical models are defined in terms of Markov properties, i.e., conditional independences, corresponding to missing edges in the graph. Thus model selection can be accomplished by testing these independences, which are equivalent to zero values of corresponding partial correlation coefficients. For concentration graphs, acyclic directed graphs, and chain graphs (both LWF and AMP classes), we apply Fisher's z-transform, Šidák's correlation inequality, and Holm's step-down...     »
Keywords:
Acyclic directed graph, Chain graph, Concentration graph, Covariance graph, DAG, Graphical model, Multiple testing
Dewey Decimal Classification:
510 Mathematik
Journal title:
Journal of Statistical Planning and Inference
Year:
2008
Journal volume:
138
Year / month:
2008-04
Quarter:
2. Quartal
Month:
Apr
Journal issue:
4
Pages contribution:
1179-1200
Language:
en
Fulltext / DOI:
doi:10.1016/j.jspi.2007.05.035
Publisher:
Elsevier BV
E-ISSN:
0378-3758
Accepted:
07.04.2007
Date of publication:
25.05.2007
Format:
Text
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