| knearneigh {spdep} | R Documentation |
The function returns a matrix with the indices of regions belonging to the set of the k nearest neighbours of each other. If longlat = TRUE, Great Circle distances are used.
knearneigh(x, k=1, longlat = NULL)
x |
matrix of region point coordinates or a SpatialPoints object |
k |
number of nearest neighbours to be returned |
longlat |
TRUE if point coordinates are longitude-latitude decimal degrees, in which case distances are measured in kilometers; if x is a SpatialPoints object, the value is taken from the object itself |
The underlying C code is based on the knn function in the class package in the VR bundle.
A list of class knn
nn |
integer matrix of region number ids |
np |
number of input points |
k |
input required k |
dimension |
number of columns of x |
x |
input coordinates |
Roger Bivand Roger.Bivand@nhh.no
example(columbus)
coords <- coordinates(columbus)
col.knn <- knearneigh(coords, k=4)
plot(columbus, border="grey")
plot(knn2nb(col.knn), coords, add=TRUE)
title(main="K nearest neighbours, k = 4")
data(state)
us48.fipsno <- read.geoda(system.file("etc/weights/us48.txt",
package="spdep")[1])
if (as.numeric(paste(version$major, version$minor, sep="")) < 19) {
m50.48 <- match(us48.fipsno$"State.name", state.name)
} else {
m50.48 <- match(us48.fipsno$"State_name", state.name)
}
xy <- as.matrix(as.data.frame(state.center))[m50.48,]
llk4.nb <- knn2nb(knearneigh(xy, k=4, longlat=FALSE))
gck4.nb <- knn2nb(knearneigh(xy, k=4, longlat=TRUE))
plot(llk4.nb, xy)
plot(diffnb(llk4.nb, gck4.nb), xy, add=TRUE, col="red", lty=2)
title(main="Differences between Euclidean and Great Circle k=4 neighbours")
summary(llk4.nb, xy, longlat=TRUE)
summary(gck4.nb, xy, longlat=TRUE)
xy1 <- SpatialPoints((as.data.frame(state.center))[m50.48,],
proj4string=CRS("+proj=longlat"))
gck4a.nb <- knn2nb(knearneigh(xy1, k=4))
summary(gck4a.nb, xy1)