On a priori error estimates of some identification methods

This paper examines in detail the estimation errors of two algorithms proposed by Koopmans [1] and Levin [2] for identifying linear systems described by an
n
th-order scalar difference equation. Necessary and sufficient conditions are established for the strong consistency of the estimates that these algorithms generate. A priori error bounds on estimation error are obtained to provide a quantitative basis for comparing these algorithms in relation to the maximum likelihood estimates. Computational results are also presented to supplement the theoretical discussions.