Abstract
In the first part of this book, we have considered in some detail the recursive estimation of parameters in linear regression models. Such models are, however, primarily utilized in the evaluation of static relationships between variables and, while they may well figure in some aspects of systems analysis (for example the characterization of equilibrium or steady state behaviour) they are not generally suitable for use in dynamic systems analysis. Of course, dynamic systems can be modelled in various ways and so consideration of methods for estimating the parameters of dynamic system models is dependent, to some extent at least, on the nature of the model chosen to characterize the system. This chapter considers a specific class of models for linear stochastic dynamic systems and shows how the recursive methods of estimation discussed in the previous chapter can be modified to handle the estimation of the parameters that characterize these models.
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© 2011 Springer-Verlag Berlin Heidelberg
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Young, P.C. (2011). Transfer Function Models and the Limitations of Recursive Least Squares. In: Recursive Estimation and Time-Series Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21981-8_6
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DOI: https://doi.org/10.1007/978-3-642-21981-8_6
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21980-1
Online ISBN: 978-3-642-21981-8
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