pwdSample: Pair-wise distance sampling
In dismo: Species Distribution Modeling

pwdSample

R Documentation

Pair-wise distance sampling

Description

Select pairs of points from two sets (without replacement) that have a similar distance to their nearest point in another set of points.

For each point in "fixed", a point is selected from "sample" that has a similar distance (as defined by threshold) to its nearest point in "reference" (note that these are likely to be different points in reference). The select point is either the nearest point nearest=TRUE, or a randomly select point nearest=FALSE that is within the threshold distance. If no point within the threshold distance is found in sample, the point in fixed is dropped.

Hijmans (2012) proposed this sampling approach to remove 'spatial sorting bias' (ssb) from evaluation data used in cross-validation of presence-only species distribution models. In that context, fixed are the testing-presence points, sample the testing-absence (or testing-background) points, and reference the training-presence points.

Usage

pwdSample(fixed, sample, reference, tr=0.33, nearest=TRUE, n=1, lonlat=TRUE, warn=TRUE)

Arguments

`fixed`	two column matrix (x, y) or (longitude/latitude) or SpatialPoints object, for point locations for which a pair should be found in `sample`
`sample`	as above for point locations from which to sample to make a pair with a point from `fixed`
`reference`	as above for reference point locations to which distances are computed
`n`	How many pairs do you want for each point in `fixed`
`tr`	Numeric, normally below 1. The threshold distance for a pair of points (one of `fixed` and one of `sample`) to their respective nearest points in `reference` to be considered a valid pair. The absolute difference in distance between the candidate point pairs in `fixed` and `reference` (dfr) and the distance between candidate point pairs in `sample` and `reference` (dsr) must be smaller than `tr` * dfr. I.e. if the dfr = 100 km, and tr = 0.1, dsr must be between >90 and <110 km to be considered a valid pair.
`nearest`	Logical. If `TRUE`, the pair with the smallest difference in distance to their nearest `reference` point is selected. If `FALSE`, a random point from the valid pairs (with a difference in distance below the threshold defined by `tr`) is selected (generally leading to higher `ssb)`
`lonlat`	Logical. Use `TRUE` if the coordinates are spherical (in degrees), and use `FALSE` if they are planar
`warn`	Logical. If `TRUE` a warning is given if `nrow(fixed) < nrow(sample)`

Value

A matrix of nrow(fixed) and ncol(n), that indicates, for each point (row) in fixed which point(s) in sample it is paired to; or NA if no suitable pair was available.

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

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)
fix <- 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)
sam <- randomPoints(r, n=50)

par(mfrow=c(1,2))
plot(sam, pch='x')
points(ref, col='red', pch=18, cex=2)
points(fix, col='blue', pch=20, cex=2)

i <- pwdSample(fix, sam, ref, lonlat=TRUE)
i
sfix <- fix[!is.na(i), ]
ssam <- sam[i[!is.na(i)], ]
ssam

plot(sam, pch='x', cex=0)
points(ssam, pch='x')
points(ref, col='red', pch=18, cex=2)
points(sfix, col='blue', pch=20, cex=2)

# try to get 3 pairs for each point in 'fixed'
pwdSample(fix, sam, ref, lonlat=TRUE, n=3)

dismo documentation built on May 31, 2023, 6:15 p.m.