knearneigh: K nearest neighbours for spatial weights

In spdep: Spatial Dependence: Weighting Schemes, Statistics and Models

Description

The function returns a matrix with the indices of points belonging to the set of the k nearest neighbours of each other. If longlat = TRUE, Great Circle distances are used. A warning will be given if identical points are found.

Usage

knearneigh(x, k=1, longlat = NULL, RANN=TRUE)

Arguments

x	matrix of 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
RANN	logical value, if the RANN package is available, use for finding k nearest neighbours when longlat is FALSE, and when there are no identical points

Details

The underlying C code is based on the knn function in the class package.

Value

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

Author(s)

Roger Bivand [e-mail]

See Also

knn, dnearneigh, knn2nb, nn2

Examples

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 +ellps=GRS80"))
gck4a.nb <- knn2nb(knearneigh(xy1, k=4))
summary(gck4a.nb, xy1)

Example output

Loading required package: sp
Loading required package: Matrix

colmbs> require(maptools)
Loading required package: maptools
Checking rgeos availability: TRUE

colmbs> columbus <- readShapePoly(system.file("etc/shapes/columbus.shp",
colmbs+  package="spdep")[1])

colmbs> col.gal.nb <- read.gal(system.file("etc/weights/columbus.gal",
colmbs+  package="spdep")[1])
Warning message:
use rgdal::readOGR or sf::st_read 
Neighbour list object:
Number of regions: 48 
Number of nonzero links: 192 
Percentage nonzero weights: 8.333333 
Average number of links: 4 
Non-symmetric neighbours list
Link number distribution:

 4 
48 
48 least connected regions:
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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 with 4 links
48 most connected regions:
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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 with 4 links
Summary of link distances:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  93.66  297.56  393.72  414.78  513.25  956.71 

  The decimal point is 2 digit(s) to the right of the |

  0 | 99
  1 | 00112233
  1 | 666699
  2 | 00222222334444444444
  2 | 6677889999
  3 | 00000111112222222233333333334444
  3 | 556666777788899999
  4 | 0000001111233
  4 | 555555666666677788888899
  5 | 0011111111122222222344444
  5 | 55666679
  6 | 00233
  6 | 5667
  7 | 011234
  7 | 5889
  8 | 022
  8 | 79
  9 | 
  9 | 56

Neighbour list object:
Number of regions: 48 
Number of nonzero links: 192 
Percentage nonzero weights: 8.333333 
Average number of links: 4 
Non-symmetric neighbours list
Link number distribution:

 4 
48 
48 least connected regions:
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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 with 4 links
48 most connected regions:
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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 with 4 links
Summary of link distances:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  93.66  297.09  393.72  410.42  508.50  953.23 

  The decimal point is 2 digit(s) to the right of the |

  0 | 99
  1 | 00112233
  1 | 666699
  2 | 00222222334444444444
  2 | 66778899999
  3 | 000000111112222222233333333334444
  3 | 5566677778888999
  4 | 0000001111233
  4 | 5555556666666777788888899
  5 | 00011111111122222223444444
  5 | 56667899
  6 | 00233
  6 | 56
  7 | 0001124
  7 | 55899
  8 | 022
  8 | 9
  9 | 
  9 | 5

NOTE: rgdal::checkCRSArgs: no proj_defs.dat in PROJ.4 shared files
Neighbour list object:
Number of regions: 48 
Number of nonzero links: 192 
Percentage nonzero weights: 8.333333 
Average number of links: 4 
Non-symmetric neighbours list
Link number distribution:

 4 
48 
48 least connected regions:
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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 with 4 links
48 most connected regions:
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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 with 4 links
Summary of link distances:
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  93.66  297.09  393.72  410.42  508.50  953.23 

  The decimal point is 2 digit(s) to the right of the |

  0 | 99
  1 | 00112233
  1 | 666699
  2 | 00222222334444444444
  2 | 66778899999
  3 | 000000111112222222233333333334444
  3 | 5566677778888999
  4 | 0000001111233
  4 | 5555556666666777788888899
  5 | 00011111111122222223444444
  5 | 56667899
  6 | 00233
  6 | 56
  7 | 0001124
  7 | 55899
  8 | 022
  8 | 9
  9 | 
  9 | 5

spdep documentation built on Aug. 19, 2017, 3:01 a.m.