Decomposable Graphical Gaussian Model Determination (1999)

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by Paolo Giudici , Peter J. Green
Citations:64 - 12 self

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50 Experiments in Stochastic Computation for High-Dimensional Graphical Models – Beatrix Jones, Carlos Carvalho, Adrian Dobra, Chris Hans, Chris Carter, Mike West - 2004
564 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
A Bayesian Approach to Model Determination for Discrete Graphical Models – Claudia Tarantola, Paolo Giudici, Peter Green - 1998
92 A characterization of Markov equivalence classes for acyclic digraphs – Steen A. Andersson, David Madigan, Michael D. Perlman - 1995
2 Bayesian Networks for Genomic Analysis – Paola Sebastiani, Maria M. Abad, Marco F. Ramoni - 2004
6 The mode oriented stochastic search (MOSS) algorithm for log-linear models with conjugate priors – Adrian Dobra, Hélène Massam - 2008
10 Efficient Model Determination for Discrete Graphical Models – Paolo Giudici, Peter Green, Claudia Tarantola - 2000
21 Model uncertainty – Merlise Clyde, Edward I. George - 2004
7 Bayesian structural learning and estimation in Gaussian graphical models – Adrian Dobra
5 Bayesian covariance matrix estimation using a mixture of decomposable graphical models. Unpublished manuscript – Helen Armstrong, Christopher K. Carter, Kevin K. F. Wong, Robert Kohn - 2005
12 Multiple testing and error control in Gaussian graphical model selection – Mathias Drton, Michael D. Perlman
227 Bayesian Graphical Models for Discrete Data – David Madigan, Jeremy York - 1993
23 A `Microscopic' Study of Minimum Entropy Search in Learning Decomposable Markov Networks – Y. Xiang, S.K.M. Wong, N. Cercone - 1995
12 Learning Bayes net structure from sparse data sets – Kevin P. Murphy - 2001
14 Bayesian inference for nondecomposable graphical Gaussian models – Petros Dellaportas, Paolo Giudici, Gareth Roberts - 2003
2 A conjugate prior for discrete hierarchical log-linear models – Hélène Massam, Jinnan Liu, Adrian Dobra - 2009
43 Optimization by learning and simulation of Bayesian and Gaussian networks – P. Larrañaga, R. Etxeberria, J. A. Lozano, J.M. Peña, J. M. Pe~na - 1999
12 Objective Bayesian model selection in Gaussian graphical models – M. Carvalho, James G. Scott - 2007
4 Probability distributions with summary graph structure – Nanny Wermuth - 2008