[R] Block clustering and largest square block in binary matrix

[Mike White]

Hi
I have a large binary square matrix (about 2500 x 2500) obtained from a
distance matrix on x (smaller simulation below), in which I want to find the
largest square block of 1's for all permutations of the rows and columns.  I
then want to remove the rows and columns corresponding to this block and
repeat the process, so that finally all the rows of data in x are assigned
to a particular square block or are isolates.  Does anyone know of a
function or algorithm that can do this?  I have looked at the blockmodel
function in the sna package but this does not appear to find the largest
block and then the next largest block etc. I have also search the email
archives without success.

rm(list=ls())
set.seed(1)
x<-rnorm(100,10,1)
d.mat<-as.matrix(dist(x))
d.mat[d.mat<=0.2]<- -1
d.mat[d.mat>0.2]<-0
d.mat<-d.mat*-1

## I have tried sorting by row and col sums does not identify the largest
squate block in every situation
rs<-rowSums(d.mat)
cs<-colSums(d.mat)
d.mat1<-d.mat[order(rs), order(cs)]

Any help would be much appreciated

Thanks
Mike White