Gibbs Partitions (EPPF's) Derived From a Stable Subordinator are Fox H and Meijer G Transforms

TL;DR

This paper provides explicit Fox-H and Meijer G function representations for the exchangeable partition probability functions (EPPFs) derived from stable subordinators, enabling precise calculations and broad generalizations.

Contribution

It introduces a novel representation of EPPFs as ratios of Fox-H and Meijer G functions, expanding the computational tools for Gibbs partitions from stable subordinators.

Findings

Conditional EPPF can be expressed as ratios of Fox-H functions.

Unconditional EPPFs can be written as H and G transforms indexed by a function h.

Explicit calculations are possible for many EPPFs, especially when h is an H or G function.

Abstract

This paper derives explicit results for the infinite Gibbs partitions generated by the jumps of an $\alpha-$stable subordinator, derived in Pitman \cite{Pit02, Pit06}. We first show that for general $\alpha$ the conditional EPPF can be represented as ratios of Fox-$H$ functions, and in the case of rational $\alpha,$ Meijer-G functions. Furthermore the results show that the resulting unconditional EPPF's, can be expressed in terms of H and G transforms indexed by a function h. Hence when h is itself a H or G function the EPPF is also an H or G function. An implication, in the case of rational $\alpha,$ is that one can compute explicitly thousands of EPPF's derived from possibly exotic special functions. This would also apply to all $\alpha$ except that computations for general Fox functions are not yet available. However, moving away from special functions, we demonstrate how results from probability theory may be used to obtain calculations. We show that a forward recursion can be applied that only requires calculation of the simplest components. Additionally we identify general classes of EPPF's where explicit calculations can be carried out using distribution theory.