Abstract
In this chapter we discuss the basic notions about state space models and their use in time series analysis. The dynamic linear model is presented as a special case of a general state space model, being linear and Gaussian. For dynamic linear models, estimation and forecasting can be obtained recursively by the well-known Kalman filter.
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© 2009 Springer-Verlag New York
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Petris, G., Petrone, S., Campagnoli, P. (2009). Dynamic linear models. In: Dynamic Linear Models with R. Use R. Springer, New York, NY. https://doi.org/10.1007/b135794_2
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DOI: https://doi.org/10.1007/b135794_2
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Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-77237-0
Online ISBN: 978-0-387-77238-7
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