On identifiability of mixtures of independent distribution laws
We consider representations of a joint distribution law of a family of categorical random variables (, a multivariate categorical variable) as a mixture of independent distribution laws (distribution laws according to which random variables are mutually independent). For infinite families of random variables, we describe a class of mixtures with identifiable mixing measure. This class is interesting from a practical point of view as well, as its structure clarifies principles of selecting a “good”...