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International Journal of Stochastic Analysis
Volume 2013 (2013), Article ID 842981, 7 pages
Research Article

A Stochastic Diffusion Process for the Dirichlet Distribution

Los Alamos National Laboratory, Los Alamos, NM 87545, USA

Received 19 December 2012; Accepted 1 March 2013

Academic Editor: Hong K. Xu

Copyright © 2013 J. Bakosi and J. R. Ristorcelli. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N coupled stochastic variables with the Dirichlet distribution as its asymptotic solution. To ensure a bounded sample space, a coupled nonlinear diffusion process is required: the Wiener processes in the equivalent system of stochastic differential equations are multiplicative with coefficients dependent on all the stochastic variables. Individual samples of a discrete ensemble, obtained from the stochastic process, satisfy a unit-sum constraint at all times. The process may be used to represent realizations of a fluctuating ensemble of N variables subject to a conservation principle. Similar to the multivariate Wright-Fisher process, whose invariant is also Dirichlet, the univariate case yields a process whose invariant is the beta distribution. As a test of the results, Monte Carlo simulations are used to evolve numerical ensembles toward the invariant Dirichlet distribution.