Abstract
In previous chapters we have encountered several models which depend on parameters that introduce parameter non-linearities into otherwise standard DLMs. Although the full class of DLMs provides an enormous variety of useful models, it is the case that, sometimes, elaborations to include models with unknown parameters result in such non-linearities, thus requiring extensions of the usual linear model analysis. Some typical, and important, examples are as follows.
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© 1989 Springer Science+Business Media New York
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West, M., Harrison, J. (1989). Non-Linear Dynamic Models. In: Bayesian Forecasting and Dynamic Models. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-9365-9_13
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DOI: https://doi.org/10.1007/978-1-4757-9365-9_13
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4757-9367-3
Online ISBN: 978-1-4757-9365-9
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