od is a wrapper around ctmm::occurrence. See help(ctmm::occurrence) for more details. rolling_od estimates occurrence distributions for a subset of a track.
rolling_od(x, ...)# S3 method for track_xyt
rolling_od(x, trast, model = "bm", res.space = 10,
res.time = 10, n.points = 5, show.progress = TRUE, ...)
od(x, ...)
# S3 method for track_xyt
od(x, trast, model = "bm", res.space = 10,
res.time = 10, ...)
[track_xyt] A track created with make_track that includes time.
Further arguments, none implemented.
[RasterLayer] A template raster for the extent and resolution of the result.
[character(1)="bm"]{"bm","ou","ouf"} The autocorrelation model that should be fit to the data. bm corresponds to Brownian motion, ou to an Ornstein-Uhlenbeck process, ouf to an Ornstein-Uhlenbeck forage process.
[numeric(1)=10] Number of grid point along each axis, relative to the average diffusion (per median timestep) from a stationary point. See also help(ctmm::occurrence).
[numeric(1)=10] Number of temproal grid points per median timestep.
[numeric(1)=5] This argument is only relevant for rolling_od and specifies the window size for the od estimation.
[logical(1)=TRUE] Indicates if a progress bar is used.
Fleming, C. H., Fagan, W. F., Mueller, T., Olson, K. A., Leimgruber, P., & Calabrese, J. M. (2016). Estimating where and how animals travel: an optimal framework for path reconstruction from autocorrelated tracking data. Ecology.