Abstract
It is shown that every probability distribution with finite entropy can be characterized as the minimum relative entropy distribution respect to a given non-negative function within a non-trivial collection of probability distributions. This result is extended to families of distributions. We also study sufficient conditions to guarantee the existence and uniqueness of a distribution with maximum entropy on certain families of distributions. Also several examples are presented of how the general results can be applied.
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