Berlin 2024 – wissenschaftliches Programm

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DY: Fachverband Dynamik und Statistische Physik

DY 26: Focus Session: Inference Methods and Biological Data (German-French Focus Session) (joint session BP/DY)

DY 26.5: Vortrag

Mittwoch, 20. März 2024, 16:15–16:30, H 2032

Model selection in stochastic dynamical systems — •Andonis Gerardos and Pierre Ronceray — Aix Marseille Univ, CNRS, CINAM, Turing Center for Living Systems, Marseille, France

Analyzing the dynamics of complex biological systems requires stochastic dynamical models; a common choice is stochastic differential equations (SDE). Given a time series, we developed a method that selects, among a class of SDE models, the one that best captures the dynamics and infers its parameters. This method corresponds to an adaptation of the Akaike information criterion (AIC) to SDE. We validated it using synthetic data generated with stochastic Lorenz and competitive Lotka-Volterra equation. Looking ahead, we envision applications of our data-driven method to unravel the hidden mechanisms of dynamical systems.

Keywords: Inference method; Model selection; Stochastic differential equation; Understanding dynamics