CONTINUOUS-TIME CORRELATED RANDOM WALK MODEL FOR ANIMAL TELEMETRY DATA

• Main Authors: Johnson, Devin S., London, Joshua M., Mary-Anne Lea, Durban, John W.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Figshare 2016
• Subjects: Environmental Science; Ecology; FOS Biological sciences; harbor seal; Northern fur seal
• Online Access: https://dx.doi.org/10.6084/m9.figshare.c.3300326.v1; https://figshare.com/collections/CONTINUOUS-TIME_CORRELATED_RANDOM_WALK_MODEL_FOR_ANIMAL_TELEMETRY_DATA/3300326/1

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 Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are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