2025/06/26 by Mallory J Flynn, Paul Gustafson, Flynn, Mallory J +1 · 1 voice · 2 citations
Biochemistry, Genetics and Molecular Biology · Environmental Science · Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #Genetic Mapping and Diversity in Plants and Animals #Genetic diversity and population structure #Wildlife Ecology and Conservation #stat.CO
paper · pdf · doi:10.48550/arxiv.2506.21023
openalex publication_date 2025/06/26 · arxiv published 2025/06/26 · arxiv updated 2025/06/26 · openalex created_date 2025/10/15 · openalex updated_date 2026/07/28
The weighted multiplier method (WMM) is an extension of the traditional method of back-calculation method to estimate the size of a target population, which synthesizes available evidence from multiple subgroups of the target population with known counts and estimated proportions by leveraging the tree-structure inherent to the data. Hierarchical Bayesian models offer an alternative to modeling population size estimation on such a structure, but require non-trivial theoretical and practical knowledge to implement. While the theory underlying the WMM methodology may be more accessible to researchers in diverse fields, a barrier still exists in execution of this method, which requires significant computation. We develop two R packages to help facilitate population size estimation on trees using both the WMM and hierarchical Bayesian modeling; AutoWMM simplifies WMM estimation for any general tree topology, and JAGStree automates the creation of suitable JAGS MCMC modeling code for these same networks.