  We consider the ensemble of n x n 0 - 1 matrices with all column and row sums
equal r. We give this ensemble the uniform weighting to construct a measure E.
We know from the work of Wanless and Pernici that E(prod_{i=1}^N
(perm_{m_i}(A)) = prod_{i=1}^N (E(perm_{m_i}(A)) * (1+ O(1/n^4)) In this paper
we prove E_1(prod_{i=1}^N (perm_{m_i}(A)) = prod_{i=1}^N (E_1(perm_{m_i}(A)) *
(1+ O(1/n^2)) where E_1 is the measure constructed on the ensemble of n x n 0 -
1 matrices with non-negative integer entries realized as the sum of r random
permutation matrices. E_1 is often used as an "approximation" to E. We have
computer evidence for
  E_1(prod_{i=1}^N (perm_{m_i}(A)) = prod_{i=1}^N (E_1(perm_{m_i}(A)) * (1+
O(1/n^4)).
