sbmNorm: (squared) norm between two stochastic block models

In graphclust: Hierarchical Graph Clustering for a Collection of Networks

(squared) norm between two stochastic block models

Description

the norm is the minimal graphon distance between two stochastic block model parameters obtained with the best permutations of the parameters

Usage

sbmNorm(theta1, theta2)

Arguments

theta1	a stochastic block model parameter
theta2	a stochastic block model parameter

Value

(squared) norm between two stochastic block models

Examples

theta1 <- list(pi=c(.5,.5), gamma=matrix((1:4)/8,2,2))
theta2 <- list(pi=c(.5,.5), gamma=matrix(4:1/8,2,2))
theta3 <- list(pi=c(.5,.5), gamma=matrix(1:4/4,2,2))
sbmNorm(theta1, theta2)
sbmNorm(theta1, theta3)
sbmNorm(theta2, theta3)

graphclust documentation built on June 7, 2023, 5:18 p.m.