# A reversible allelic partition process and Pitman sampling formula

## TL;DR

This paper introduces a new continuous-time Markov chain model for dynamic allelic partitions that extends existing sampling formulas, maintains mutual dependence over time, and exhibits reversible behavior with a stationary distribution.

## Contribution

It presents a novel Markov chain model extending the Pitman sampling formula, capturing reversible dynamics and asymptotic behavior in allelic partition processes.

## Key findings

- The model maintains mutual dependence among multiplicities over time.
- When death rate exceeds birth rate, the system has a reversible distribution.
- The population converges to a stationary configuration with finite families and individuals.

## Abstract

We introduce a continuous-time Markov chain describing dynamic allelic partitions which extends the branching process construction of the Pitman sampling formula in Pitman (2006) and the birth-and-death process with immigration studied in Karlin and McGregor (1967), in turn related to the celebrated Ewens sampling formula. A biological basis for the scheme is provided in terms of a population of individuals grouped into families, that evolves according to a sequence of births, deaths and immigrations. We investigate the asymptotic behaviour of the chain and show that, as opposed to the birth-and-death process with immigration, this construction maintains in the temporal limit the mutual dependence among the multiplicities. When the death rate exceeds the birth rate, the system is shown to have reversible distribution identified as a mixture of Pitman sampling formulae, with negative binomial mixing distribution on the population size. The population therefore converges to a stationary random configuration, characterised by a finite number of families and individuals.