Abstract

The stochastic bifurcation process, which partitions a unit into its positive fractions z 1, …, Z I ; such that z 1, + … + zI , = 1, is characterized by a topology and probability law governing the (I – 1) bifurcations. Aside from describing many natural phenomena, such as flows in dendritic networks, the stochastic bifurcation process also offers a device for generating families of multivariate distributions on the (I – 1)-dimensional simplex. In particular, the process with independent bifurcations governed by beta laws gives rise to the generalized Dirichlet family. Every member of this family is identified by the three-tuple: (1) the bifurcation topology, (2) the permutation of fractions, and (3) the parameters of the beta laws. Successively smaller subsets of bifurcation topologies, containing all possible topologies, only double-cascaded topologies, and only cascaded topologies, lead to progressively narrower distribution families of Types A, B, and C. Type C is the Connor-Mosimann distribution, whi...

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