Spatial neighbour sparse representation
listw2sn.RdThe function makes a "spatial neighbour" object representation
(similar to the S-PLUS spatial statististics module representation of a
"listw" spatial weights object. sn2listw() is the inverse function to listw2sn(), creating a "listw" object from a "spatial neighbour" object.
Arguments
- listw
a
listwobject from for examplenb2listw- sn
a
spatial.neighbourobject- style
default NULL, missing, set to "M" and warning given; if not "M", passed to
nb2listwto re-build the object- zero.policy
default NULL, use global option value; if FALSE stop with error for any empty neighbour sets, if TRUE permit the weights list to be formed with zero-length weights vectors
- from_mat2listw
default FALSE, set TRUE if called from
mat2listw
Value
listw2sn()returns a data frame with three columns, and with class spatial.neighbour:
- from
region number id for the start of the link (S-PLUS row.id)
- to
region number id for the end of the link (S-PLUS col.id)
- weights
weight for this link
Author
Roger Bivand Roger.Bivand@nhh.no
Examples
columbus <- st_read(system.file("shapes/columbus.gpkg", package="spData")[1], quiet=TRUE)
col.gal.nb <- read.gal(system.file("weights/columbus.gal", package="spData")[1])
col.listw <- nb2listw(col.gal.nb)
col.listw$neighbours[[1]]
#> [1] 2 3
col.listw$weights[[1]]
#> [1] 0.5 0.5
col.sn <- listw2sn(col.listw)
str(col.sn)
#> Classes ‘spatial.neighbour’ and 'data.frame': 230 obs. of 3 variables:
#> $ from : int 1 1 2 2 2 3 3 3 3 4 ...
#> $ to : int 2 3 1 3 4 1 2 4 5 2 ...
#> $ weights: num 0.5 0.5 0.333 0.333 0.333 ...
#> - attr(*, "n")= int 49
#> - attr(*, "region.id")= chr [1:49] "1" "2" "3" "4" ...
#> - attr(*, "neighbours.attrs")= chr [1:7] "class" "region.id" "GeoDa" "gal" ...
#> - attr(*, "weights.attrs")= chr [1:3] "mode" "W" "comp"
#> - attr(*, "GeoDa")=List of 2
#> ..$ shpfile: chr NA
#> ..$ ind : chr NA
#> - attr(*, "listw.call")= language nb2listw(neighbours = col.gal.nb)