Description Usage Arguments Value References Examples
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.
1 |
A |
a list of length N containing (M\times M) adjacency matrices. |
out.dist |
a logical; |
K |
the number of bins for the spectrum interval [0,2]. |
wN |
a decaying exponent; default is 4 set by authors. |
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_weighted_2010NetworkDistance
1 2 3 4 5 6 7 8 9 10 11 12 | ## 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)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.