Some exactly solvable models of urn process theory.

*(English)* Zbl 1193.60011
Fourth colloquium on mathematics and computer science IV. Algorithms, trees, combinatorics and probabilities. Papers based on the presentations at the colloquium, Nancy, France, September 18--22, 2006. Nancy: The Association. Discrete Mathematics & Theoretical Computer Science (DMTCS). Discrete Mathematics and Theoretical Computer Science. Proceedings, 59-118, electronic only (2006).

Summary: We establish a fundamental isomorphism between discrete-time balanced urn processes and certain ordinary differential systems, which are nonlinear, autonomous, and of a simple monomial form. As a consequence, all balanced urn processes with balls of two colours are proved to be analytically solvable in finite terms. The corresponding generating functions are expressed in terms of certain Abelian integrals over curves of the Fermat type (which are also hypergeometric functions), together with their inverses. A consequence is the unification of the analyses of many classical models, including those related to the coupon collector’s problem, particle transfer (the Ehrenfest model), Friedman’s “adverse campaign” and Pólya’s contagion model, as well as the OK Corral model (a basic case of Lanchester’s theory of conflicts). In each case, it is possible to quantify very precisely the probable composition of the urn at any discrete instant. We study here in detail “semi-sacrificial” urns, for which the following are obtained: a Gaussian limiting distribution with speed of convergence estimates as well as a characterization of the large and extreme large deviation regimes. We also work out explicitly the case of 2-dimensional triangular models, where local limit laws of the stable type are obtained. A few models of dimension three or greater, e.g., “autistic” (generalized Pólya), cyclic chambers (generalized Ehrenfest), generalized coupon-collector, and triangular urns, are also shown to be exactly solvable. For the entire collection see [

Zbl 1189.68002].

##### MSC:

60C05 | Combinatorial probability |