Modeling Animal Communication Using Multivariate Hawkes Processes with Additive Excitation and Multiplicative Inhibition
Bokgyeong Kang, Erin M. Schliep, Alan E. Gelfand, Ariana Strandburg-Peshkin, and Robert S. Schick

TL;DR
This paper introduces a flexible multivariate Hawkes process model combining additive excitation and multiplicative inhibition to analyze animal communication, enabling clearer interpretation of excitation and inhibition effects.
Contribution
It proposes a novel Hawkes process formulation that incorporates inhibition without losing interpretability, and demonstrates its effectiveness on real animal communication data.
Findings
Meerkat calls show significant excitation and inhibition effects.
Whale data primarily exhibit within-species excitation.
Model provides a clear quantification of background and excitation contributions.
Abstract
Animal acoustic communication often exhibits temporal dependence, with calls triggering or suppressing subsequent calls within and across call types, individuals, or species. While Hawkes processes provide a natural framework for modeling excitation, incorporating inhibition in multivariate settings can raise identifiability issues and complicate parameter interpretation. We propose a flexible class of multivariate Hawkes processes that combines additive excitation with multiplicative inhibition. This formulation preserves the branching process interpretation of excitation while reducing confounding between excitation and inhibition, and allows direct quantification of background and excitation contributions to the event rate. Bayesian inference is conducted via Markov chain Monte Carlo, and model adequacy is assessed using the random time change theorem. The proposed methodology is…
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Taxonomy
TopicsMarine animal studies overview · Underwater Acoustics Research · Speech and Audio Processing
