ssb: Spatial sorting bias

In dismo: Species Distribution Modeling

Description

Determine "spatial sorting bias", or the difference between two point data sets in the average distance to the nearest point in a reference dataset.

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 use FALSE 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

Author(s)

Robert J. Hijmans

References

Hijmans, R.J., 2012. Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null-model. Ecology 93: 679-688.

See Also

pwdSample

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]

Example output

Loading required package: raster
Loading required package: sp
NOTE: rgdal::checkCRSArgs: no proj_defs.dat in PROJ.4 shared files
NOTE: rgdal::checkCRSArgs: no proj_defs.dat in PROJ.4 shared files
NOTE: rgdal::checkCRSArgs: no proj_defs.dat in PROJ.4 shared files
NOTE: rgdal::checkCRSArgs: no proj_defs.dat in PROJ.4 shared files
            p        a
[1,] 1502.956 5023.704
[1] 0.2991729

dismo documentation built on May 2, 2019, 6:07 p.m.