calSim {BCSub}

Function to calculate the similarity matrix based on the cluster membership indicator of each iteration.

Description

Function to calculate the similarity matrix based on the cluster membership indicator of each iteration.

Usage

calSim(mat)

Arguments

mat

A matrix of cluster membership indicators.

Value

returns a similarity matrix.

Examples

n = 90 ## number of subjects
iters = 200 ## number of iterations
## matrix of cluster membership indicators
## perfect clustering with three clusters
mat = matrix(rep(1:3,each=n/3),nrow=n,ncol=iters)
sim = calSim(t(mat))
## plot similarity matrix
x <- rep(1:n,times=n)
y <- rep(1:n,each=n)
z <- as.vector(sim)
levelplot(z~x*y,col.regions=rev(gray.colors(n^2)), xlab = "Subject ID",ylab = "Subject ID")