CONTINUOUS‐TIME CORRELATED RANDOM WALK MODEL FOR ANIMAL TELEMETRY DATA

作者：Devin L. Johnson, Josh M. London, Mary‐Anne Lea, John W. Durban · 发表于：Ecology · 年份：2008 · DOI：10.1890/07-1032.1 · 被引用次数：690 · 研究领域：Marine animal studies overview、Target Tracking and Data Fusion in Sensor Networks、Wildlife Ecology and Conservation

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 Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are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