A1178
Title: Parametric, nonparametric and repulsive mixture models for ecological data
Authors: Eleni Matechou - University of Kent (United Kingdom) [presenting]
Abstract: Ecological surveys often track individuals or species to monitor time-varying processes such as migration patterns and changes in behavioral or life states. Mixture models are a suitable and flexible approach for analyzing such data, and they have been used extensively in the field. Parametric, nonparametric, and repulsive mixture models are discussed for different types of ecological data and present results for case studies on species monitored using standard count data, as well as data collected on individuals using new technologies.
