Simulates a random latent matrix Z given its expectation, dyadic correlation and censored binary nomination data
rZ_cbin_fc(Z, EZ, rho, Y, odmax, odobs)
a square matrix, the new value of Z
a square matrix, the current value of Z
expected value of Z
dyadic correlation
square matrix of ranked nomination data
a scalar or vector giving the maximum number of nominations for each individual
observed outdegree
Peter Hoff
simulates Z under the constraints (1) Y[i,j]=1, Y[i,k]=0 => Z[i,j]>Z[i,k] , (2) Y[i,j]=1 => Z[i,j]>0 , (3) Y[i,j]=0 & odobs[i]<odmax[i] => Z[i,j]<0