multiviewtest (version 2.0.1)

mv_sbm_gmm_gen: Generates data from a stochastic block model for a network view and a multivariate view

Description

Generates data from a stochastic block model for a network view and a multivariate view with n observations. The data for the multivariate view is drawn from a Gaussian mixture model.

Usage

mv_sbm_gmm_gen(n, Pi, theta1, mu2, Sigma2, sparse = FALSE)

Arguments

n

number of observations

Pi

K1 x K2 matrix where the (k, k')th entry contains the probability of an observation belonging to community k in View 1 and cluster k' in View 2

theta1

K1 x K1 matrix containing the between-community edge probabilities for View 1

mu2

mu2 p2 x K2 matrix where the columns contain the K2 cluster means in View 2

Sigma2

p2 x p2 matrix containing the covariance matrix for View 2

sparse

If true, return matrix views in sparseMatrix format

Value

A list containing the following components:

data

A list with two items: the view 1 n x n adjacency matrix and the view 2 n x p multivariate data set

communities

A list with two items: the view 1 community memberships and the view 2 cluster memberships

References

Gao, L.L., Witten, D., Bien, J. Testing for Association in Multi-View Network Data, preprint.

Examples

# NOT RUN {
# 50 draws from a stochastic block model for a network view and a multivariate view
# where the communities and the clusters are independent
n <- 50
Pi <- tcrossprod(c(0.5, 0.5), c(0.5, 0.5))
theta1 <- rbind(c(0.5, 0.1), c(0.1, 0.5))
mu2 <- cbind(c(2, 2), c(-2, 2))
Sigma2 <- diag(rep(0.5, 2))

mv_sbm_gmm_gen(n, Pi, theta1, mu2, Sigma2)

# }