Abstract
The behavioural framework has several attractions to offer for the identification of multivariable systems. Some of the variables may be left unexplained without the need for a distinction between inputs and outputs; criteria for model quality are independent of the chosen parametrization; and behaviours allow for a global (i.e., non-local) approximation of the system dynamics. This is illustrated by the identification of dynamic factor models. Behavioural least squares is a natural method for this problem, and a comparison is given with non-behavioural methods.
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