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- Title:
A New Algorithm for Maximum Likelihood Estimation in Gaussian Graphical Models for Marginal Independence
- Document type:
- Zeitschriftenaufsatz
- Author(s):
- Drton, Mathias; Richardson, Thomas S.
- Abstract:
- Graphical models with bi-directed edges (<->) represent marginal independence: the absence of an edge between two vertices indicates that the corresponding variables are marginally independent. In this paper, we consider maximum likelihood estimation in the case of continuous variables with a Gaussian joint distribution, sometimes termed a covariance graph model. We present a new fitting algorithm which exploits standard regression techniques and establish its convergence properties. Moreover, we contrast our procedure to existing estimation methods
- Dewey Decimal Classification:
- 510 Mathematik
- Congress title:
- 19th Conference on Uncertainty in Artificial Intelligence (UAI 2003)
- Congress / additional information:
- August 7-10, 2003; Acapulco, Mexico
- Journal title:
- Proceedings of the 19th Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-03)
- Year:
- 2003
- Pages contribution:
- 184-191
- Language:
- en
- WWW:
- UAI
- Publisher:
- Morgan Kaufmann
- Publisher address:
- San Francisco, CA, USA
- Print-ISSN:
- 0-127-05664-5
- Format:
- Text
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