  An estimated state-space model can possibly be improved by further iterations
with estimation data. This contribution specifically studies if models obtained
by subspace estimation can be improved by subsequent re-estimation of the B, C,
and D matrices (which involves linear estimation problems). Several tests are
performed, which shows that it is generally advisable to do such further
re-estimation steps using the maximum likelihood criterion. Stated more
succinctly in terms of MATLAB functions, ssest generally outperforms n4sid.
