# On Poisson approximations for the Ewens sampling formula when the mutation parameter grows with the sample size

## TL;DR

This paper investigates Poisson approximations for the Ewens sampling formula when the mutation parameter increases with the sample size, expanding understanding of its asymptotic properties in this regime.

## Contribution

It advances the analysis of the Ewens sampling formula by studying its asymptotic behavior with a growing mutation parameter using Poisson approximation techniques.

## Key findings

- Asymptotic properties of the total number of alleles analyzed
- Distribution of component counts approximated by Poisson distributions
- New results for the case where mutation parameter grows with sample size

## Abstract

The Ewens sampling formula was firstly introduced in the context of population genetics by Warren John Ewens in 1972, and has appeared in a lot of other scientific fields. There are abundant approximation results associated with the Ewens sampling formula especially when one of the parameters, the sample size $n$ or the mutation parameter $\theta$ which denotes the scaled mutation rate, tends to infinity while the other is fixed. By contrast, the case that $\theta$ grows with $n$ has been considered in a relatively small number of works, although this asymptotic setup is also natural. In this paper, when $\theta$ grows with $n$, we advance the study concerning the asymptotic properties of the total number of alleles and of the counts of components in the allelic partition assuming the Ewens sampling formula from the viewpoint of Poisson approximations.