Consistency and Central Limit Results for the Maximum Likelihood Estimator in the Admixture Model

In the Admixture Model, the probability of an individual having a certain number of alleles at a specific marker depends on the allele frequencies in $K$ ancestral populations and the fraction of the individual's genome originating from these ancestral populations. This study investigates consistency and central limit results of maximum likelihood estimators (MLEs) for the ancestry and the allele frequencies in the Admixture Model, complimenting previous work by \cite{pfaff2004information, pfaffelhuber2022central}. Specifically, we prove consistency of the MLE, if we estimate the allele frequencies and the ancestries. Furthermore, we prove central limit theorems, if we estimate the ancestry of a finite number of individuals and the allele frequencies of finitely many markers, also addressing the case where the true ancestry lies on the boundary of the parameter space. Finally, we use the new theory to quantify the uncertainty of the MLEs for the data of \citet{10002015global}.

Publication Details

Journal
ArXiv.org
Published
2025-07-25
Primary Topic
Genetic Associations and Epidemiology
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article
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article

Consistency and Central Limit Results for the Maximum Likelihood Estimator in the Admixture Model

ArXiv.org
Genetic Associations and Epidemiology
article

Consistency and Central Limit Results for the Maximum Likelihood Estimator in the Admixture Model

article en

Abstract

In the Admixture Model, the probability of an individual having a certain number of alleles at a specific marker depends on the allele frequencies in $K$ ancestral populations and the fraction of the individual's genome originating from these ancestral populations. This study investigates consistency and central limit results of maximum likelihood estimators (MLEs) for the ancestry and the allele frequencies in the Admixture Model, complimenting previous work by \cite{pfaff2004information, pfaffelhuber2022central}. Specifically, we prove consistency of the MLE, if we estimate the allele frequencies and the ancestries. Furthermore, we prove central limit theorems, if we estimate the ancestry of a finite number of individuals and the allele frequencies of finitely many markers, also addressing the case where the true ancestry lies on the boundary of the parameter space. Finally, we use the new theory to quantify the uncertainty of the MLEs for the data of \citet{10002015global}.

ArXiv.org
Openalex Percentile: Top 40%
Genetic Associations and Epidemiology
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