Abstract Details
Activity Number:
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696
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Type:
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Contributed
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Date/Time:
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Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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Abstract #315979
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View Presentation
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Title:
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A GLARE Algorithm for Selecting Gaussian Graphical Models
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Author(s):
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George Terrell*
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Companies:
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Virginia Tech
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Keywords:
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conditional independence ;
multivariate normal ;
model selection ;
LARS
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Abstract:
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Sparse Gaussian graphical models are useful ways of simplifying multivariate data, so that only a few of the pairwise associations need to be taken into account. Inspired by the Generalized Least Angle Regression algorithm from linear regression, we build the model by forward selection of the entries in the precision matrix that must be nonzero in order to account for observed correlations.
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Authors who are presenting talks have a * after their name.
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