nd_edd function

Edge Difference Distance

It is of the most simplest form that Edge Difference Distance (EDD) takestwo adjacency matrices and takes Frobenius norm of their differnces.

nd.edd(A, out.dist = TRUE)

Arguments

• A: a list of length $N$ containing $(M\times M)$ adjacency matrices.
• out.dist: a logical; TRUE for computed distance matrix as a dist object.

Returns

a named list containing

• D: an $(N\times N)$ matrix or dist object containing pairwise distance measures.

Examples

## load example data
data(graph20)

## compute distance matrix
output = nd.edd(graph20, out.dist=FALSE)

## visualize
opar <- par(no.readonly=TRUE)
par(pty="s")
image(output$D[,20:1], main="two group case", axes=FALSE, col=gray(0:32/32))
par(opar)

References

Rdpack::insert_ref(key="hammond_graph_2013",package="NetworkDistance")