Definition 4. Let $\mathcal{E}_1 , \mathcal{E}_2 , \dots, \mathcal{E}_n$ be n events on a probability space $Ω$. The dependency graph is a directed graph $D = (V, E)$ on the set of vertices $V = {1, \dots , n} $ (corresponding to $\mathcal{E}_1 , \mathcal{E}_2 , \dots, \mathcal{E}_n$ ) if for each $1 ≤ i ≤ n, \mathcal{E}_i$ is mutually independent of all the events $\{\mathcal{E}_j : (i, j) \notin E\}$.
Note that the dependency graph is not unique. For instance, consider two independent coin flips with outcome H or T. Consider the events
$$\mathcal{E}_1 := \{(H, H), (H, T )\} \text{ (first coin flip is H)},$$
$$\mathcal{E}_2 := \{(H, H), (T, H)\} \text{ (second coin flip is H)},$$
$$\mathcal{E}_3 := \{(H, H), (T, T )\} \text{ (both coin flips are the same)}.$$
Then, two possible dependency graphs are as follows(for the left graph, the low-right vertex should be $\mathcal E_3$.):
In the example, if I am correct, the three events $\mathcal{E}_1, \mathcal{E}_2, \mathcal{E}_3$ are pairwise independent but not mutually independent. But the first dependency graph shows that $\mathcal{E}_1$ is mutually independent of $\mathcal{E}_3$, $\mathcal{E}_2$ is mutually independent of $\mathcal{E}_1$, and $\mathcal{E}_3$ is mutually independent of $\mathcal{E}_2$. The second dependency graph shows that $\mathcal{E}_1$ is mutually independent of $\mathcal{E}_3$, $\mathcal{E}_3$ is mutually independent of $\mathcal{E}_1$, and $\mathcal{E}_2$ is mutually independent of $\mathcal{E}_1$.
- So it seems like a dependency graph of a set of events doesn't necessarily need to capture all the dependence or independence relation between events?
In a dependency graph of a set of events, does existence of an edge from $A_i$ to $A_j$ imply that $A_i$ is not mutually independent of $A_j$? I think no, because in the example, the three events are pairwise independent, but there are edges between some two of them.
Is the concept an event being mutually independent of another event not a symmetric relation between events? Our usual definition for mutual independence between two events are $P(\mathcal{E}_1 \cap \mathcal{E}_2) = P(\mathcal{E}_1) P(\mathcal{E}_2)$, which seems to be a symmetric relation between events.
More generally, any directed graph with minimum out degree 1 is a dependency graph.
If all events $\mathcal{E}_1 , \mathcal{E}_2 , \dots, \mathcal{E}_n$ are mutually independent, then the empty graph is a dependency graph.
Why is a directed graph with "minimum out degree 1" singled out in particular?
Thanks and regards!
\mathcal E
. $\endgroup$