Circles range

Description

The Circles Range model predicts that a species is present at sites within a certain distance from a training point, and absent further away.

Usage

1
2
3
4
5
## S4 method for signature 'matrix'
circles(p, d, lonlat, n=360, r=6378137, dissolve=TRUE, ...)

## S4 method for signature 'SpatialPoints'
circles(p, d, lonlat, n=360, r=6378137, dissolve=TRUE, ...)

Arguments

p

point locations (presence). Two column matrix, data.frame or SpatialPoints* object

d

numeric. The radius of each circle in meters. A single number of a vector with elements corresponding to rows in p. If missing the diameter is computed from the mean inter-point distance

lonlat

logical. Are these longitude/latitude data? If missing this is taken from the p if it is a SpatialPoints* object

n

integer. How many vertices in the circle? Default is 360

r

numeric. Radius of the earth. Only relevant for longitude/latitude data. Default is 6378137 m

dissolve

logical. Dissolve overlapping circles. Setting this to FALSE may be useful for plotting overlapping circles

...

additional arguments, none implemented

Value

An object of class 'CirclesRange' (inherits from DistModel-class)

Author(s)

Robert J. Hijmans

See Also

predict, geoDist, convHull, maxent, domain, mahal, convexHull

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
r <- raster(system.file("external/rlogo.grd", package="raster"))
#presence data
pts <- matrix(c(17, 42, 85, 70, 19, 53, 26, 84, 84, 46, 48, 85, 4, 95, 48, 54, 66,
 74, 50, 48, 28, 73, 38, 56, 43, 29, 63, 22, 46, 45, 7, 60, 46, 34, 14, 51, 70, 31, 39, 26), ncol=2)
train <- pts[1:12, ]
test <- pts[13:20, ]
				 
cc <- circles(train, lonlat=FALSE)
predict(cc, test)

plot(r)
plot(cc, border='red', lwd=2, add=TRUE)
points(train, col='red', pch=20, cex=2)
points(test, col='black', pch=20, cex=2)

pr <- predict(cc, r, progress='')
plot(r, legend=FALSE)
plot(pr, add=TRUE, col='blue')
points(test, col='black', pch=20, cex=2)
points(train, col='red', pch=20, cex=2)


# to get the polygons:
p <- polygons(cc)
p

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.