mat2listw: Convert a square spatial weights matrix to a weights list...
In spdep: Spatial Dependence: Weighting Schemes, Statistics and Models

Description Usage Arguments Value Author(s) See Also Examples

The function converts a square spatial weights matrix, optionally a sparse matrix to a weights list object, optionally adding region IDs from the row names of the matrix, as a sequence of numbers 1:nrow(x), or as given as an argument. The style can be imposed by rebuilting the weights list object internally.

1	mat2listw(x, row.names = NULL, style="M")

`x`	A square non-negative matrix with no NAs representing spatial weights; may be a matrix of class “sparseMatrix”
`row.names`	row names to use for region IDs
`style`	default "M", unknown style; if not "M", passed to `nb2listw` to re-build the object

A listw object with the following members:

`style`	"M", meaning matrix style, underlying style unknown, or assigned style argument in rebuilt object
`neighbours`	the derived neighbours list
`weights`	the weights for the neighbours derived from the matrix

Roger Bivand Roger.Bivand@nhh.no

nb2listw, nb2mat

example(columbus)
coords <- coordinates(columbus)
col005 <- dnearneigh(coords, 0, 0.5, attr(col.gal.nb, "region.id"))
summary(col005)
col005.w.mat <- nb2mat(col005, zero.policy=TRUE)
col005.w.b <- mat2listw(col005.w.mat)
summary(col005.w.b$neighbours)
diffnb(col005, col005.w.b$neighbours)
col005.w.mat.3T <- kronecker(diag(3), col005.w.mat)
col005.w.b.3T <- mat2listw(col005.w.mat.3T, style="W")
summary(col005.w.b.3T$neighbours)
W <- as(nb2listw(col005, style="W", zero.policy=TRUE), "CsparseMatrix")
col005.spM <- mat2listw(W)
summary(col005.spM$neighbours)
diffnb(col005, col005.spM$neighbours)
IW <- kronecker(Diagonal(3), W)
col005.spM.3T <- mat2listw(IW, style="W")
summary(col005.spM.3T$neighbours)

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: 49 
Number of nonzero links: 170 
Percentage nonzero weights: 7.080383 
Average number of links: 3.469388 
4 regions with no links:
1 3 6 21
Link number distribution:

 0  1  2  3  4  5  6  7  8  9 
 4 11  5  8  3  9  2  2  3  2 
11 least connected regions:
2 5 9 10 31 34 36 39 42 46 47 with 1 link
2 most connected regions:
11 16 with 9 links
Neighbour list object:
Number of regions: 49 
Number of nonzero links: 170 
Percentage nonzero weights: 7.080383 
Average number of links: 3.469388 
4 regions with no links:
1 3 6 21
Link number distribution:

 0  1  2  3  4  5  6  7  8  9 
 4 11  5  8  3  9  2  2  3  2 
11 least connected regions:
2 5 9 10 31 34 36 39 42 46 47 with 1 link
2 most connected regions:
11 16 with 9 links
Neighbour list object:
Number of regions: 49 
Number of nonzero links: 0 
Percentage nonzero weights: 0 
Average number of links: 0 
49 regions with no links:
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 49
Warning message:
In nb2listw(res$neighbours, glist = res$weights, style = style,  :
  zero sum general weights
Neighbour list object:
Number of regions: 147 
Number of nonzero links: 510 
Percentage nonzero weights: 2.360128 
Average number of links: 3.469388 
12 regions with no links:
1 3 6 21 50 52 55 70 99 101 104 119
Link number distribution:

 0  1  2  3  4  5  6  7  8  9 
12 33 15 24  9 27  6  6  9  6 
33 least connected regions:
2 5 9 10 31 34 36 39 42 46 47 51 54 58 59 80 83 85 88 91 95 96 100 103 107 108 129 132 134 137 140 144 145 with 1 link
6 most connected regions:
11 16 60 65 109 114 with 9 links
Warning message:
In sn2listw(df) : 1, 3, 6, 21 are not origins
Neighbour list object:
Number of regions: 49 
Number of nonzero links: 170 
Percentage nonzero weights: 7.080383 
Average number of links: 3.469388 
4 regions with no links:
1 3 6 21
Link number distribution:

 0  1  2  3  4  5  6  7  8  9 
 4 11  5  8  3  9  2  2  3  2 
11 least connected regions:
2 5 9 10 31 34 36 39 42 46 47 with 1 link
2 most connected regions:
11 16 with 9 links
Neighbour list object:
Number of regions: 49 
Number of nonzero links: 0 
Percentage nonzero weights: 0 
Average number of links: 0 
49 regions with no links:
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 49
Note: method with signature 'diagonalMatrix#Matrix' chosen for function 'kronecker',
 target signature 'ddiMatrix#dgCMatrix'.
 "ANY#sparseMatrix" would also be valid
Note: method with signature 'dsparseMatrix#dsparseMatrix' chosen for function 'kronecker',
 target signature 'dtTMatrix#dgCMatrix'.
 "TsparseMatrix#sparseMatrix" would also be valid
Warning messages:
1: In sn2listw(df) :
  1, 3, 6, 21, 50, 52, 55, 70, 99, 101, 104, 119 are not origins
2: In nb2listw(res$neighbours, glist = res$weights, style = style,  :
  zero sum general weights
Neighbour list object:
Number of regions: 147 
Number of nonzero links: 510 
Percentage nonzero weights: 2.360128 
Average number of links: 3.469388 
12 regions with no links:
1 3 6 21 50 52 55 70 99 101 104 119
Link number distribution:

 0  1  2  3  4  5  6  7  8  9 
12 33 15 24  9 27  6  6  9  6 
33 least connected regions:
2 5 9 10 31 34 36 39 42 46 47 51 54 58 59 80 83 85 88 91 95 96 100 103 107 108 129 132 134 137 140 144 145 with 1 link
6 most connected regions:
11 16 60 65 109 114 with 9 links