They both use similar techniques of retransmission, and consequently do not satisfy the independence conditions that would allow to separately add their gains.
The maximal joint entropy corresponds to independence conditions of the random variables Y and X i.e. when the JPD is factorized p(Y, X) = p(Y p X).
On the other hand, merging operators violate the independence conditions, one of the requirements imposed on aggregation functions in the impossibility theorems.
They also argue that AQFT's satisfaction of various independence conditions including local commutativity shows that it is consistent with the assumption that spacelike separated regions have their own distinct states.
The simulated series satisfactorily captures the characteristics of averaging or common data (i.e. with low or moderate speed) and, under certain independence conditions, the directional extreme value distribution of the wind speed is also properly reproduced.
Similarly to probability models, which are embedded in influence diagrams as a Bayesian network, preferential/utility independence conditions can be used to factor the joint utility function into small factors and reduce the number of parameters needed to fully define the joint function.
