nd.wsd {NetworkDistance} | R Documentation |
Normalized Laplacian matrix contains topological information of
a corresponding network via its spectrum. nd.wsd
adopts weighted
spectral distribution of eigenvalues and brings about a metric via
binning strategy.
nd.wsd(A, out.dist = TRUE, K = 50, wN = 4)
A |
a list of length |
out.dist |
a logical; |
K |
the number of bins for the spectrum interval |
wN |
a decaying exponent; default is |
a named list containing
an (N\times N)
matrix or dist
object containing pairwise distance measures.
an (N\times M)
matrix of rows being eigenvalues for each graph.
Fay D, Haddadi H, Thomason A, Moore AW, Mortier R, Jamakovic A, Uhlig S, Rio M (2010). “Weighted Spectral Distribution for Internet Topology Analysis: Theory and Applications.” IEEE/ACM Transactions on Networking, 18(1), 164–176. ISSN 1063-6692, 1558-2566.
## load example data and extract a few
data(graph20)
gr.small = graph20[c(1:5,11:15)]
## compute distance matrix
output = nd.wsd(gr.small, out.dist=FALSE, K=10)
## visualize
opar = par(no.readonly=TRUE)
par(pty="s")
image(output$D[,10:1], main="two group case", axes=FALSE, col=gray(0:32/32))
par(opar)