Self-exciting point process models
Speaker: Charlotte Jones-Todd, University of Auckland, New Zealand
Abstract: Modelling spatial and temporal patterns in ecology is imperative to understand the complex processes inherent in ecological phenomena. Log-Gaussian Cox processes are a popular choice amongst ecologists, used to describe the spatiotemporal distribution of point-referenced data. In addition, self-exciting point pattern models are becoming increasingly popular to infer the contagious nature of events (e.g., animal sightings, cue rates). In this talk, I will present extensions to these well-known models that include spatiotemporal self-excitation and joint likelihood models. Such models are, often, better equipped to capture the complex mechanisms inherent in many ecological and environmental data.