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Continuous-time correlated random walk model for animal telemetry data
journal contributionposted on 2023-05-16, 21:48 authored by Johnson, DS, London, JM, Mary-Anne LeaMary-Anne Lea, Durban, JW
We propose a continuous-time version of the correlated random walk model for animal telemetry data. The continuous-time formulation allows data that have been nonuniformly collected over time to be modeled without subsampling, interpolation, or aggregation to obtain a set of locations uniformly spaced in time. The model is derived from a continuous-time Ornstein-Uhlenbeck velocity process that is integrated to form a location process. The continuous-time model was placed into a state–space framework to allow parameter estimation and location predictions from observed animal locations. Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are possible. A harbor seal data set was analyzed with a model that incorporates the proportion of each hour spent on land. Also, a northern fur seal pup data set was analyzed with a random drift component to account for directed travel and ocean currents.
Department/SchoolSchool of Natural Sciences
PublisherEcological Society of America
Place of publicationUnited States
Rights statementCopyright 2008 by the Ecological Society of America