Hammersley–Clifford
Theorem taught in Graphical models, part of Statistical learning
Hammersley–Clifford
| Type | Theorem |
| Taught in | Graphical models |
| Part | Statistical learning |
A probability distribution with positive and continuous density f with respect to a product measure satisfies the pairwise Markov property with respect to an undirected graph G if and only if it factorises according to G.
Used in
- Taught in Graphical models, where the derivation and examples are.
- All 8 questions on Graphical models
See also
Markov properties and factorisation · Undirected graph · Clique · A zero precision entry is conditional independence · Maximum likelihood for a known graph · Graphical lasso · Markov graphs · Graph terminology