Content deleted Content added
rv attempt to correct "descendent/ancestor" |
No edit summary |
||
Line 13:
:P(''X<sub>i</sub>'' | parents of ''X<sub>i</sub>'') for ''i'' = 1,...,''n''.
In other words, the [[probability distribution|joint distribution]] factors into a product of conditional distributions. The graph structure indicates direct dependencies among random variables. Any two nodes that are not in a descendant/ancestor relationship are [[Conditional independence|conditionally independent]] given the values of their parents.
This type of graphical model is known as a directed graphical model, Bayesian network, or belief network. There are also undirected graphical models, a.k.a. Markov networks, in which graph separation encodes conditional independencies (these are also known as Graphical Gaussian models, or GGMs). A recent application of graphical models is to describe [[gene regulatory network]]s.
{{math-stub}}
| |||