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Activity Number: 311 - Statistical Models in Ecology
Type: Contributed
Date/Time: Tuesday, July 31, 2018 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract #330134 Presentation
Title: A Dynamic Individual-Based Model of Ant Interaction Events
Author(s): Nathan Wikle* and Ephraim Hanks and David Hughes
Companies: and The Pennsylvania State University and Pennsylvania State University
Keywords: animal behavior; dynamic networks; Markov process; Bayesian; ecology

Ants are inherently social insects whose observed feeding behavior (i.e., trophallaxis events) can be represented as a dynamic, high frequency contact network. Traditional statistical analyses of network models often aggregate data over time. However, in doing so, the information contained in data observed at high frequencies may be lost. We present a continuous-time dynamic network model based on a continuous-time Markov process, with states being defined by the network topology, and transition rates modeled as a function of individual (node-specific) and pairwise (edge-specific) covariates measured over time. We demonstrate this model on data consisting of observed trophallaxis events among a colony of common black carpenter ants, collected over 14400 seconds.

Authors who are presenting talks have a * after their name.

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