ssb
From dismo v1.14
by Robert Hijmans
Spatial sorting bias
Determine "spatial sorting bias", or the difference between two point data sets in the average distance to the nearest point in a reference dataset.
 Keywords
 spatial
Usage
ssb(p, a, reference, lonlat=TRUE, avg=TRUE)
Arguments
 p
 two column matrix (x, y) or (longitude/latitude) or SpatialPoints object, for point locations
 a
 two column matrix (x, y) or (longitude/latitude) or SpatialPoints object, for point locations
 reference
 as above for reference point locations to which distances are computed
 lonlat
 Logical. Use
TRUE
if the coordinates are spherical (in degrees), and useFALSE
if they are planar  avg
 Logical. If
TRUE
the distances are averaged
Value

matrix with two values. 'dp': the average distance from a point in
p
to the nearest point in reference
and 'da': the average distance from a point in a
to the nearest point in reference
.
Distance is in meters if lonlat=TRUE
, and in mapunits (typically also meters) if lonlat=FALSE
References
Hijmans, R.J., 2012. Crossvalidation of species distribution models: removing spatial sorting bias and calibration with a nullmodel. Ecology 93: 679688.
See Also
Examples
ref < matrix(c(54.5,38.5, 2.5, 9.5, 45.5, 1.5, 9.5, 4.5, 10.5, 10.5), ncol=2)
p < matrix(c(56.5, 30.5, 6.5, 14.5, 25.5, 48.5, 14.5, 2.5, 14.5,
11.5, 17.5, 11.5), ncol=2)
r < raster()
extent(r) < c(110, 110, 45, 45)
r[] < 1
set.seed(0)
a < randomPoints(r, n=50)
b < ssb(p, a, ref)
# distances in km
b / 1000
# an index of spatial sorting bias (1 is no bias, near 0 is extreme bias)
b[1] / b[2]
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