get analytic expressions of expectations, variances and covariances
theo_mu_sig(E, n1, n2, weights)the expectation of the between-sample edge-count.
the expectation of the within-sample edge-count for sample 1.
the expectation of the within-sample edge-count for sample 2.
the variance of the between-sample edge-count.
the variance of the within-sample edge-count for sample 1.
the variance of the within-sample edge-count for sample 2.
the covariance of the within-sample edge-counts.
an edge matrix representing a similarity graph. Each row represents an edge and records the indices of two ends of an edge in two columns. The indices of observations in sample 1 are from 1 to n1 and indices of observations in sample 2 are from 1+n1 to n1+n2.
number of observations in sample 1
number of observations in sample 2
weights assigned to each edges