nb2blocknb

0th

Percentile

Block up neighbour list for location-less observations

The function blocks up a neighbour list for known spatial locations to create a new neighbour list for multiple location-less observations know to belong to the spatial locations, using the identification tags of the locations as the key.

Keywords
spatial
Usage
nb2blocknb(nb=NULL, ID, row.names = NULL)
Arguments
nb
an object of class nb with a list of integer vectors containing neighbour region number ids; if null, an nb object with no neighbours is created the length of unique(as.character(ID))
ID
identification tags of the locations for the location-less observations;

sort(unique(as.character(ID))) must be identical to

sort(as.character(attr(nb, "region.id")));

same length as row.names if provided.

row.names
character vector of observation ids to be added to the neighbours list as attribute region.id, default seq(1, nrow(x)); same length as ID if provided.
Details

Assume that there is a list of unique locations, then a neighbour list can build for that, to create an input neighbour list. This needs to be "unfolded", so that observations belonging to each unique location are observation neighbours, and observations belonging to the location neighbours of the unique location in question are also observation neighbours, finally removing the observation itself (because it should not be its own neighbour). This scenario also arises when say only post codes are available, and some post codes contain multiple observations, where all that is known is that they belong to a specific post code, not where they are located within it (given that the post code locations are known).

Value

The function returns an object of class nb with a list of integer vectors containing neighbour observation number ids.

See Also

knn2nb, dnearneigh, cell2nb, tri2nb, poly2nb

Aliases
  • nb2blocknb
Examples
## Not run: 
# data(boston)
# summary(as.vector(table(boston.c$TOWN)))
# townaggr <- aggregate(boston.utm, list(town=boston.c$TOWN), mean)
# block.rel <- graph2nb(relativeneigh(as.matrix(townaggr[,2:3])),
#  as.character(townaggr[,1]), sym=TRUE)
# block.rel
# print(is.symmetric.nb(block.rel))
# plot(block.rel, as.matrix(townaggr[,2:3]))
# points(boston.utm, pch=18, col="lightgreen")
# block.nb <- nb2blocknb(block.rel, as.character(boston.c$TOWN))
# block.nb
# print(is.symmetric.nb(block.nb))
# plot(block.nb, boston.utm)
# points(boston.utm, pch=18, col="lightgreen")
# n.comp.nb(block.nb)$nc
# moran.test(boston.c$CMEDV, nb2listw(boston.soi))
# moran.test(boston.c$CMEDV, nb2listw(block.nb))
# block.nb <- nb2blocknb(NULL, as.character(boston.c$TOWN))
# block.nb
# print(is.symmetric.nb(block.nb))
# plot(block.nb, boston.utm)
# n.comp.nb(block.nb)$nc
# moran.test(boston.c$CMEDV, nb2listw(block.nb, zero.policy=TRUE), zero.policy=TRUE)
# ## End(Not run)
Documentation reproduced from package spdep, version 0.6-9, License: GPL (>= 2)

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