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Activity Number:
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177
- Observations Through a Foggy Lens: Modeling Complex Measurement Error and Non-Random Missingness in Ecological and Environmental Health Data
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Type:
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Invited
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Date/Time:
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Monday, August 8, 2022 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Consulting
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Abstract #319250
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Title:
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Detecting Changes in Dynamic Social Networks Using Multiply Labeled Movement Data
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Author(s):
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Zaineb L. Boulil and Henry Scharf* and John W. Durban and Holly Fearnbach and Trevor W. Joyce and Samantha G. M. Leander
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Companies:
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Rady Children's Hostpital and San Diego State University and Southall Environmental Associates, Inc. and Sr3 SeaLife Response, Rehabilitation and Research and Environmental Assessment Services and Southall Environmental Associates, Inc.
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Keywords:
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social network;
movement data;
drone-gathered data
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Abstract:
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The social structure of an animal population can often influence movement and inform researchers on a species’ behavioral tendencies. Animal social networks can be studied through movement data; however, modern sources of data can have identification issues that result in multiply-labeled individuals. Since all available social movement models rely on unique labels, we extend an existing Bayesian hierarchical movement model in a way that makes use of a latent social network and accommodates multiply-labeled movement data (MLMD). We apply our model to drone-measured movement data from Risso’s dolphins (Grampus griseus) and estimate the effects of sonar exposure on the dolphins’ social structure. Our proposed framework can be applied to MLMD for various social movement applications.
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Authors who are presenting talks have a * after their name.
