gs.sims.er: Erdos-Renyi Graphs

In neurodata/graphstats: Graph Statistics

Description

A function to simulate graphs from the Erdos-Renyi Random Graph Model.

Usage

gs.sims.er(n, v, priors = c(0.5, 0.5), p = c(0.5, 0.5))

Arguments

n	the number of graphs to simulate.
v	the number of vertices.
priors	the composition of the graphs in each class as a length K vector. Defaults to c(0.5, 0.5). Note that K=length(priors) is the number of classes of graphs, and sum(priors) will be normalized to 1.
p	the probability of an edge existing for each class, as a length K vector. Defaults to c(0.5, 0.5). Note that K=length(p) is the number of classes of graphs, and 0 <= p <= 1.

Value

An object of class "Simulation" containing the following:

graphs	[[n]][v, v] the n graphs with v vertices as a list of adjacency matrices.
Y	[n] the class labels for each of the n graphs.

Author(s)

Eric Bridgeford

neurodata/graphstats documentation built on May 14, 2019, 5:19 p.m.