dw_track {alphahull} | R Documentation |
RBM-sausage calculation of tracking data
Description
This function approximates the RBM-sausage of tracking data and returns a list of geom_path objects of the boundary.
Usage
dw_track(x, y = NULL, eps, nps = 20000, sc = 100)
Arguments
x , y |
The |
eps |
Value of |
nps |
Number of points to generate in each segment connecting two locations, see Details. |
sc |
Scale factor. |
Details
An attempt is made to interpret the arguments x and y in a way suitable for computing the RBM-sausage. Any reasonable way of defining the coordinates is acceptable, see xy.coords
.
Given a trajectory in the plane, the estimator is defined as the set of points whose distance to the trajectory is less than or equal to \epsilon
(this estimator is analogous to the one of Devroye and Wise (1980) for i.i.d. data). Increase nps
if the trajectory is not contained in the computed estimator.
Value
A list of geom_path objects defining the boundary of the estimator
References
Cholaquidis, A., Fraiman, R., Lugosi, G. and Pateiro-Lopez, B. (2014) Set estimation from reflected Brownian motion. arXiv:1411.0433.
Devroye, L. and Wise, G. (1980) Detection of abnormal behaviour via nonparametric estimation of the support. SIAM J. Appl. Math. 3, pp. 480-488.
Wikelski, M., and Kays, R. (2014). Movebank: archive, analysis and sharing of animal movement data. World Wide Web electronic publication.
Examples
## Not run:
library(move)
library(ggmap)
# Data from Movebank
# Study Name: Dunn Ranch Bison Tracking Project
# Principal Investigator: Stephen Blake, Randy Arndt, Doug Ladd
# Max Planck Institute for Ornithology Radolfzell Germany
study <- "Dunn Ranch Bison Tracking Project"
cainfo <- system.file("CurlSSL", "cacert.pem", package = "RCurl")
options(RCurlOptions = list(verbose = FALSE, capath = cainfo, ssl.verifypeer = FALSE))
# Login to movebank (first create the login object)
curl <- movebankLogin(username = "xxx", password = "zzz")
# Downloads study stored in Movebank
track <- getMovebankData(study = study, login = curl)
dat <- track@data[track@data[, "deployment_id"] == 13848432,]
# Map of animal locations
bbox <- ggmap::make_bbox(dat[,"location_long"], dat[,"location_lat"], f = 0.3)
map_loc <- get_map(location = bbox, source = "google", maptype = 'satellite')
map <- ggmap(map_loc, extent = 'panel', maprange=FALSE)
p <- map + geom_path(data = dat, aes(x = location_long, y = location_lat), col=2, size=0.3)
p
ah_dw <- dw_track(x = dat[, c("location_long", "location_lat")], eps = 0.001)
p + ah_dw
## End(Not run)