For a given graph, returns the specified neighborhood structure at the selected order(s).
1 2 3 
dat 
one or more graphs. 
order 
order of the neighborhood to extract. 
neighborhood.type 
neighborhood type to employ. 
mode 

diag 
logical; do the diagonal entries of 
thresh 
dichotomization threshold to use for 
return.all 
logical; return neighborhoods for all orders up to 
partial 
logical; return partial (rather than cumulative) neighborhoods? 
The adjacency matrix associated with the ith order neighborhood is defined as the identity matrix for order 0, and otherwise depends on the type of neighborhood involved. For input graph G=(V,E), let the base relation, R, be given by the underlying graph of G (i.e., G U G^T) if total neighborhoods are sought, the transpose of G if incoming neighborhoods are sought, or G otherwise. The partial neighborhood structure of order i>0 on R is then defined to be the digraph on V whose edge set consists of the ordered pairs (j,k) having geodesic distance i in R. The corresponding cumulative neighborhood is formed by the ordered pairs having geodesic distance less than or equal to i in R.
Neighborhood structures are commonly used to parameterize various types of network autocorrelation models. They may also be used in the calculation of certain types of local structural indices; gapply
provides an alternative function which can be used for this purpose.
An array or adjacency matrix containing the neighborhood structures (if dat
is a single graph); if dat
contains multiple graphs, then a list of such structures is returned.
Carter T. Butts buttsc@uci.edu
gapply
, nacf
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15  #Draw a random graph
g<rgraph(10,tp=2/9)
#Show the total partial outneighborhoods
neigh<neighborhood(g,9,neighborhood.type="out",return.all=TRUE)
par(mfrow=c(3,3))
for(i in 1:9)
gplot(neigh[i,,],main=paste("Partial Neighborhood of Order",i))
#Show the total cumulative outneighborhoods
neigh<neighborhood(g,9,neighborhood.type="out",return.all=TRUE,
partial=FALSE)
par(mfrow=c(3,3))
for(i in 1:9)
gplot(neigh[i,,],main=paste("Cumulative Neighborhood of Order",i))

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