Abstract
SUMMARY This paper proposes an approach to the simultaneous identification and estimation of transfer function models. An estimation procedure is advanced consisting of a sequence of four ordinary least squares calculations and the asymptotic properties of each step are presented, consistency and asymptotic efficiency being shown. A strategy for the identification of the model structure based on a selection criterion that arises naturally from the last step of the estimation algorithm is also investigated. Consideration is given to the numerical implementation of the techniques discussed, and finally a practical example is employed to illustrate the methods.
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