Generalised Poisson-Dirichlet Distributions and the Negative Binomial Point Process

Abstract

When $S=(S_t)_{t\ge 0}$ is an $\alpha$-stable subordinator, the sequence of ordered jumps of $S$, up till time $1$, omitting the $r$ largest of them, and taken as proportions of their sum $^{(r)}S_t$, defines a 2-parameter distribution on the infinite dimensional simplex, $\nabla_{\infty}$, which we call the $\mathrm{PD}_\alpha^{(r)}$ distribution. When $r=0$ it reduces to the $\mathrm{PD}_\alpha$ distribution introduced by Kingman in 1975. We observe a serendipitous connection between $\mathrm{PD}_\alpha^{(r)}$ and the negative binomial point process of Gregoire (1984), which we exploit to analyse in detail a size-biased version of $\mathrm{PD}_\alpha^{(r)}$. As a consequence we derive a stick-breaking representation for the process and a useful form for its distribution. This program produces a large new class of distributions available for a variety of modelling purposes.