Ewen's sampling formula is a foundational theoretical result that connects probability and number theory with molecular genetics and molecular evolution; it was the analytical result required for testing the neutral theory of evolution, and has since been directly or indirectly utilized in a number of population genetics statistics. Ewen's sampling formula, in turn, is deeply connected to Stirling numbers of the first kind. Here, we explore the cumulative distribution function of these Stirling numbers, which enables a single direct estimate of the sum, using representations in terms of the incomplete beta function. This estimator enables an improved method for calculating an asymptotic estimate for one useful statistic, Fu's [Formula: see text] By reducing the calculation from a sum of terms involving Stirling numbers to a single estimate, we simultaneously improve accuracy and dramatically increase speed.

Asymptotic analysis, Cumulative distribution functions, Evolutionary inference, Numerical algorithms, Population genetics statistics, Stirling numbers of the first kind
G3 (Bethesda, Md.)
Centrum Wiskunde & Informatica, Amsterdam, The Netherlands

Chen, S.L, & Temme, N.M. (2020). A Faster and More Accurate Algorithm for Calculating Population Genetics Statistics Requiring Sums of Stirling Numbers of the First Kind. G3 (Bethesda, Md.), 10(11), 3959–3967. doi:10.1534/g3.120.401575