Dynamic Grooming Networks in Baboon Troops

• Activity Number: 33
• Type: Contributed
• Date/Time: Sunday, August 3, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Bailey Fosdick*+ and Yingbo Li and David Banks and Susan Alberts
• Companies: SAMSI and Clemson University and Duke University and Duke University
• Keywords: latent space model ; Bayesian methods ; population fission ; dynamic network

Abstract

Baboon troops are intriguing social populations as they have strict social hierarchies and about once every fifteen years a given troop will fission into two new troops. Often this occurs according to matrilineal or patrilineal lines, but once in a while, neither of these familial patterns is exhibited. In these cases, primatologists are greatly interested in understanding the severance process and determining whether temporal data on baboon grooming activities may foreshadow the fission event and eventual troop memberships. Current network models are inadequate for modeling such data since they cannot readily account for variable intensity of observation across time and baboons, and they lack a natural mechanism that allows for social distancing over time and prediction of future grooming. In this talk, we present a dynamic latent space network model that addresses these issues. We describe Bayesian procedures developed for model estimation and demonstrate our methodology on data from a baboon troop in the Amboseli National Reserve in Kenya.