Computo<p>The second paper of January 2025 in Computo, by Daphné Giorgi, Sarah Kaakai and Vincent Lemaire, introduces the R package IBMPopSim, which facilitates the simulation of the random evolution of heterogeneous populations using stochastic Individual-Based Models (IBMs). </p><p>The package relies on a unified mathematical framework, based on thinning of Poisson measures, for the simulation of IBMs where individuals are represented by their birth date, death date (+∞ if none), and a collection of features. It uses Rcpp for efficiency.</p><p>The paper introduces this mathematical framework, gives a detailed overview of the IBMPopSim package, and illustrates it on two use cases, one from actuarial sciences and the other from population genetics.</p><p>On this last example, the authors show that their randomized algorithm is one or two orders of magnitudes faster than the full algorithm.</p><p>The paper is available with (of course) R code at: <a href="https://doi.org/10.57750/sfxn-1t05" target="_blank" rel="nofollow noopener noreferrer" translate="no"><span class="invisible">https://</span><span class="">doi.org/10.57750/sfxn-1t05</span><span class="invisible"></span></a></p><p><a href="https://mathstodon.xyz/tags/populationDynamics" class="mention hashtag" rel="tag">#<span>populationDynamics</span></a> <a href="https://mathstodon.xyz/tags/openScience" class="mention hashtag" rel="tag">#<span>openScience</span></a> <a href="https://mathstodon.xyz/tags/openAccess" class="mention hashtag" rel="tag">#<span>openAccess</span></a> <a href="https://mathstodon.xyz/tags/openSource" class="mention hashtag" rel="tag">#<span>openSource</span></a> <a href="https://mathstodon.xyz/tags/Rstats" class="mention hashtag" rel="tag">#<span>Rstats</span></a></p>