sample_correlated_gnp: Generate a new random graph from a given graph by randomly
adding/removing edges

Description

Sample a new graph by perturbing the adjacency matrix of a given graph
and shuffling its vertices.

Usage

sample_correlated_gnp(old.graph, corr, p = old.graph$p, permutation = NULL)

Arguments

old.graph

The original graph.

corr

A scalar in the unit interval, the target Pearson
correlation between the adjacency matrices of the original the generated
graph (the adjacency matrix being used as a vector).

p

A numeric scalar, the probability of an edge between two
vertices, it must in the open (0,1) interval.

permutation

A numeric vector, a permutation vector that is
applied on the vertices of the first graph, to get the second graph. If
NULL, the vertices are not permuted.

Value

An unweighted graph of the same size as old.graph such
that the correlation coefficient between the entries of the two
adjacency matrices is corr. Note each pair of corresponding
matrix entries is a pair of correlated Bernoulli random variables.

Details

Please see the reference given below.

References

Lyzinski, V., Fishkind, D. E., Priebe, C. E. (2013). Seeded
graph matching for correlated Erdos-Renyi graphs.
http://arxiv.org/abs/1304.7844