nd_edd: Edge Difference Distance

Description Usage Arguments Value References Examples

Description

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

Usage

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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.

Value

a named list containing

D

an (N\times N) matrix or dist object containing pairwise distance measures.

References

\insertRef

hammond_graph_2013NetworkDistance

Examples

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## 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)

NetworkDistance documentation built on Aug. 21, 2021, 5:07 p.m.