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6
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Separation An Completeness Properties For Amp Chain Graph Markov Models
– Michael Levitz, Michael D. Perlman, David Madigan
- 2000
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71
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A characterization of Markov equivalence classes for acyclic digraphs
– Steen A. Andersson, David Madigan, Michael D. Perlman
- 1995
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58
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ANCESTRAL GRAPH MARKOV MODELS
– Thomas Richardson, Peter Spirtes
- 2002
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32
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Chain Graph Models and their Causal Interpretations
– Steffen L. Lauritzen, Thomas S. Richardson
- 2001
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7
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On Recovery Algorithm for Chain Graphs
– Milan Studeny
- 1997
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7
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Chain Graphs: Semantics and Expressiveness
– Remco R. Bouckaert, Milan Studeny
- 1995
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36
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An Alternative Markov Property for Chain Graphs
– Steen Andersson, David Madigan, Michael Perlman
- 1996
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22
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Using Path Diagrams as a Structural Equation Modelling Tool
– Peter Spirtes, Thomas Richardson, Chris Meek, Richard Scheines, Clark Glymour
- 1997
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8
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A graphical characterization of lattice conditional independence models
– Steen A. Andersson, David Madigan, Michael D. Perlman, Christopher M. Triggs
- 1997
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46
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Causal Inference from Graphical Models
– Steffen L Lauritzen
- 2001
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4
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Characterizing Markov equivalence classes for AMP chain graph models
– A. Andersson, Michael D. Perlman
- 2005
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35
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Bayesian Model Averaging And Model Selection For Markov Equivalence Classes Of Acyclic Digraphs
– David Madigan, Steen Andersson, Michael Perlman, Chris Volinsky
- 1996
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24
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Chain Graphs for Learning
– Wray Buntine
- 1995
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1
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Sequences of regressions and their independences
– Nanny Wermuth, Kayvan Sadeghi
- 2012
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|
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Sequences of regressions and their dependences
– Nanny Wermuth
|
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20
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A SINful approach to Gaussian graphical model selection
– Mathias Drton, Michael, D. Perlman
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7
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Multiple testing and error control in Gaussian graphical model selection
– Mathias Drton, Michael D. Perlman
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10
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Local computation in hypertrees
– Glenn Shafer, Prakash P. Shenoy
- 1991
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156
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A Guide to the Literature on Learning Probabilistic Networks From Data
– Wray Buntine
- 1996
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