Efficient simulation of individual-based population models

Daphné Giorgi, Sarah Kaakai, Vincent Lemaire 2025-01-27

Citation

Daphné Giorgi, Sarah Kaakai and Vincent Lemaire (January 2025). Efficient simulation of individual-based population models. Computo. https://doi.org/10.57750/sfxn-1t05

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Authors’ affiliations

• Daphné Giorgi (Sorbonne Université, CNRS)
• Sarah Kaakai (Université Sorbonne Paris Nord, CNRS, Ecole Polytechnique, CNRS)
• Vincent Lemaire (Sorbonne Université, CNRS)

Abstract

The R Package IBMPopSim facilitates the simulation of the random evolution of heterogeneous populations using stochastic Individual-Based Models (IBMs). The package enables users to simulate population evolution, in which individuals are characterized by their age and some characteristics, and the population is modified by different types of events, including births/arrivals, death/exit events, or changes of characteristics. The frequency at which an event can occur to an individual can depend on their age and characteristics, but also on the characteristics of other individuals (interactions). Such models have a wide range of applications in fields including actuarial science, biology, ecology or epidemiology. IBMPopSim overcomes the limitations of time-consuming IBMs simulations by implementing new efficient algorithms based on thinning methods, which are compiled using the Rcpp package while providing a user-friendly interface.