Graphical representation of independence structures
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Summary
A unifying interpretation of independence structure for LMGs is defined and the equivalence of pairwise and global Markov properties for graphoids defined over the nodes of RGs is proved, enabling the derivation of algorithms to generate these graphs from a given DAG or from a graph of a specific subclass.
- Type
- dissertation
- Published
- 2012-01-01
- Cited by
- 6
- References
- 50
- Access
- Open access
- OpenAlex
- https://openalex.org/W799170909
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:19569439
Keywords
Indifference graph, Chordal graph, Modular decomposition, Directed acyclic graph, Combinatorics
References
- The dimensionality of mixed ancestral graphs
- Conditional Independence in Statistical Theory
- The igraph software package for complex network research
- Marginalizing and conditioning in graphical models
- On the Markov equivalence of maximal ancestral graphs
- Linear Dependencies Represented by Chain Graphs
- Markov properties for mixed graphs
- Characterizing Markov equivalence classes for AMP chain graph models
- On chain graph models for description of conditional independence structures
- Elementary Principles in Statistical Mechanics
- Stable mixed graphs
- Triangular systems for symmetric binary variables
- Independence properties of directed markov fields
- Decomposable Models: A New Look at Interdependence and Dependence Structures in Psychological Research.
- Partial inversion for linear systems and partial closure of independence graphs
- Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative
- Discrete chain graph models
- A THEOREM ABOUT RANDOM FIELDS
- The Method of Path Coefficients
- PROBABILITY DISTRIBUTIONS WITH SUMMARY GRAPH STRUCTURE
Cited by
- Markov properties for mixed graphs
- Stable mixed graphs
- Probabilistic Graphical Model Structure Learning: Application to Multi-Label Classification. (Apprentissage de Structure de Modèles Graphiques Probabilistes: Application à la Classification Multi-Label)
- Constraint-based causal discovery from multiple interventions over overlapping variable sets
- Interventional Markov Equivalence for Mixed Graph Models
- Markov properties for mixed graphs
- Stable mixed graphs
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