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Continuous-Time Correlated Random Walk Model for Animal Telemetry Data

Devin S. Johnson, Joshua M. London, Mary-Anne Lea and John W. Durban
Ecology
Vol. 89, No. 5 (May, 2008), pp. 1208-1215
Published by: Wiley
Stable URL: http://www.jstor.org/stable/27651667
Page Count: 8
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Continuous-Time Correlated Random Walk Model for Animal Telemetry Data
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Abstract

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 Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are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.

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