rnsbm: simulation of a graph according the noisy stochastic block...

In noisySBM: Noisy Stochastic Block Mode: Graph Inference by Multiple Testing

Description

simulation of a graph according the noisy stochastic block model

Usage

rnsbm(n, theta, modelFamily = "Gauss", directed = FALSE)

Arguments

n	number of nodes
theta	model parameters of the noisy stochastic block model pi latent block proportions, Q-vector w connectivity parameters, N_Q-vector nu0 parameters of the null distribution nu parameters of the alternative distribution
modelFamily	probability distribution for the edges. Possible values: Gauss, Gamma, Poisson
directed	indicates if the graph is directed (boolean)

Value

a list with:

dataMatrix

simulated matrix from the noisy stochastic block model

theta

model parameters of the noisy stochastic block model

latentZ

underlying latent node memberships

latentAdj

underlying latent binary graph

Examples

n <- 10
Q <- 2
theta <- list(pi= rep(1/Q,Q), nu0=c(0,1))
theta$nu <- matrix(c(-2,10,-2, 1,1,1),nrow=Q*(Q+1)/2,ncol=2)
theta$w <- c(.5, .9, .3)
obs <- rnsbm(n, theta, modelFamily='Gauss')
obs

noisySBM documentation built on Dec. 16, 2020, 5:09 p.m.