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.

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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
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article

Asymptotics of the allele frequency spectrum and the number of alleles

Soudabeh Shemehsavar, Ross Maller
Journal of Applied Probability
Bayesian Methods and Mixture Models
article

Asymptotics of the allele frequency spectrum and the number of alleles

Soudabeh Shemehsavar, Ross Maller
article en

Abstract

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.

Journal of Applied ProbabilityVol. 62(2)
Australian National University (AU), Murdoch University (AU), University of Tehran (IR)
Openalex Percentile: Top 81%
Bayesian Methods and Mixture Models
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