Dynamic Models of Animal Movement with Spatial Point Process Interactions

James C. Russell (), Ephraim M. Hanks and Murali Haran
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James C. Russell: Pennsylvania State University
Ephraim M. Hanks: Pennsylvania State University
Murali Haran: Pennsylvania State University

Journal of Agricultural, Biological and Environmental Statistics, 2016, vol. 21, issue 1, No 2, 22-40

Abstract: Abstract When analyzing animal movement, it is important to account for interactions between individuals. However, statistical models for incorporating interaction behavior in movement models are limited. We propose an approach that models dependent movement by augmenting a dynamic marginal movement model with a spatial point process interaction function within a weighted distribution framework. The approach is flexible, as marginal movement behavior and interaction behavior can be modeled independently. Inference for model parameters is complicated by intractable normalizing constants. We develop a double Metropolis–Hastings algorithm to perform Bayesian inference. We illustrate our approach through the analysis of movement tracks of guppies (Poecilia reticulata).

Keywords: Auxiliary variable MCMC algorithm; Collective motion; Biased correlated random walk; Group navigation; Poecilia reticulata; State-space model (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s13253-015-0219-0

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