NetworkDistance (version 0.3.6)

nd.csd: \(L_2\) Distance of Continuous Spectral Densities

Description

The method employs spectral density of eigenvalues from Laplacian in that for each, we have corresponding spectral density \(\rho(w)\) as a sum of narrow Lorentz distributions with bandwidth parameter. Since it involves integration of a function over the non-compact domain, it may blow up to infinity and the code automatically aborts the process.

Usage

nd.csd(A, out.dist = TRUE, bandwidth = 1)

Value

a named list containing

D

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

spectra

an \((N\times M-1)\) matrix where each row is top-\(M-1\) vibrational spectra.

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.

bandwidth

common bandwidth of positive real number.

References

ipsen_evolutionary_2002NetworkDistance

Examples

# \donttest{
## load example data
data(graph20)

## compute distance matrix
output = nd.csd(graph20, out.dist=FALSE, bandwidth=1.0)

## 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)
# }