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These functions allow the extraction of the home-range contours computed using various methods (kernel home range, cluster home range, etc.)
getverticeshr(x, percent = 95, …)
# S3 method for estUD
getverticeshr(x, percent = 95, ida = NULL, unin = c("m", "km"),
unout = c("ha", "km2", "m2"),
standardize = FALSE, …)
# S3 method for estUDm
getverticeshr(x, percent = 95, whi = names(x),
unin = c("m", "km"),
unout = c("ha", "km2", "m2"),
standardize = FALSE, …)
# S3 method for MCHu
getverticeshr(x, percent = 95, whi = names(x), …)
# S3 method for default
getverticeshr(x, percent = 95, …)
For getverticeshr.estUD
, an object of class
estUD
. For getverticeshr.estUDm
, an object of class
estUDm
. For getverticeshr.MCHu
, an object of class
MCHu
.
a single value giving the percentage level for home-range estimation
a character string indicating the id of the polygons
corresponding to the home range in the resulting
SpatialPolygonsDataFrame
(see the help page of
SpatialPolygonsDataFrame
). By default it is set to
"homerange"
the units of the relocations coordinates. Either "m" for meters (default) or "km" for kilometers
the units of the output areas. Either "m2" for square meters, "km2" for square kilometers or "ha" for hectares (default)
a vector of character strings indicating which animals should be returned.
a logical value indicating whether the UD should be standardized over the area of interest, so that the volume under the UD and *over the area* is equal to 1..
Additional arguments to be passed to and from other methods
An object of class SpatialPolygonsDataFrame
containing the
selected home range contours of the animals.
kernelUD
, kernelbb
or
kernelkc
for methods generating objects of classes
estUD
and estUDm
,
clusthr
, LoCoH.a
and
CharHull
for methods generating objects of class
MCHu
.
# NOT RUN {
### Example with a kernel home range
data(puechabonsp)
loc <- puechabonsp$relocs
## have a look at the data
head(as.data.frame(loc))
## the first column of this data frame is the ID
## Estimation of UD for the four animals
(ud <- kernelUD(loc[,1]))
## Calculates the home range contour
ver <- getverticeshr(ud, percent=95)
ver
plot(ver)
## Example with a cluster home range
clu <- clusthr(loc[,1])
ver2 <- getverticeshr(clu, percent=95)
ver2
plot(ver2)
# }
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