mcp  R Documentation 
mcp
computes the home range of several
animals using the Minimum Convex Polygon estimator.
mcp.area
is used for homerange size estimation.
hr.rast
is used to rasterize a minimum convex polygon.
plot.hrsize
is used to display the homerange size estimated at
various levels.
mcp(xy, percent=95, unin = c("m", "km"),
unout = c("ha", "km2", "m2"))
mcp.area(xy, percent = seq(20,100, by = 5),
unin = c("m", "km"),
unout = c("ha", "km2", "m2"), plotit = TRUE)
hr.rast(mcp, w)
## S3 method for class 'hrsize'
plot(x, ...)
xy 
An object inheriting the class 
percent 
A single number for the function 
unin 
the units of the relocations coordinates. Either

unout 
the units of the output areas. Either 
plotit 
logical. Whether the plot should be drawn. 
x 
an objet of class 
mcp 
an objet of class 
w 
an objet of class 
... 
additional arguments to be passed to the function

This function computes the Minimum Convex Polygon estimation after the
removal of (100 minus percent)
percent of the relocations the
farthest away from the centroid of the home range (computed by the
arithmetic mean of the coordinates of the relocations for each
animal).
mcp
returns an object of class SpatialPolygonsDataFrame
,
in which the first column contains the ID of the animals, and the
second contains the home range size.
mcp.area
returns a data frame of class hrsize
,
with one column per animal and one row per level of
estimation of the home range.
hr.rast
returns an object of class
SpatialPixelsDataFrame
.
Clement Calenge clement.calenge@ofb.gouv.fr
Mohr, C.O. (1947) Table of equivalent populations of north american small mammals. The American Midland Naturalist, 37, 223249.
chull
,
SpatialPolygonsDataFrameclass
for additionnal
information on the class SpatialPolygonsDataFrame
.
data(puechabonsp)
rel < puechabonsp$relocs
## estimates the MCP
cp < mcp(rel[,1])
## The homerange size
as.data.frame(cp)
## Plot the home ranges
plot(cp)
## ... And the relocations
plot(rel, col=as.data.frame(rel)[,1], add=TRUE)
## Computation of the homerange size:
cuicui1 < mcp.area(rel[,1])
## Rasterization
ii < hr.rast(cp, puechabonsp$map)
opar < par(mfrow=c(2,2))
lapply(1:4, function(i) {image(ii, i); box()})
par(opar)
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