Asymptotics of the allele frequency spectrum and the number of alleles
Abstract We derive large-sample and other limiting distributions of components of the allele frequency spectrum vector, $\mathbf{M}_n$ , joint with the number of alleles, $K_n$ , from a sample of n genes. Models analysed include those constructed from gamma and $\alpha$ -stable subordinators by Kingman (thus including the Ewens model), the two-parameter extension by Pitman and Yor, and a two-parameter version constructed by omitting large jumps from an $\alpha$ -stable subordinator. In each case the limiting distribution of a finite number of components of $\mathbf{M}_n$ is derived, joint with $K_n$ . New results include that in the Poisson–Dirichlet case, $\mathbf{M}_n$ and $K_n$ are asymptotically independent after centering and norming for $K_n$ , and it is notable, especially for statistical applications, that in other cases the limiting distribution of a finite number of components of $\mathbf{M}_n$ , after centering and an unusual $n^{\alpha/2}$ norming, conditional on that of $K_n$ , is normal.
Authors
- Soudabeh Shemehsavar (ORCID: https://orcid.org/0000-0002-8742-9357)
- Ross Maller (ORCID: https://orcid.org/0000-0001-8563-9898)
Institutions
- Australian National University (AU)
- Murdoch University (AU)
- University of Tehran (IR)
Publication Details
- Journal
- Journal of Applied Probability
- Published
- 2024-11-22
- DOI
- https://doi.org/10.1017/jpr.2024.84
- Primary Topic
- Bayesian Methods and Mixture Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00