Abstract
There is a large amount of literature on applications of the Kalman filter model, which is used for estimation of unobservable variables. As for applications, we can consider a time-varying parameter model, an estimation of seasonal components, an estimation of autoregressive-moving average (ARMA) model, prediction of final data and so on. Thus, the Kalman filter is particularly powerful and useful in the model that includes unobservable components.
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© 1996 Springer-Verlag Berlin Heidelberg
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Tanizaki, H. (1996). Introduction. In: Nonlinear Filters. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-03223-7_1
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DOI: https://doi.org/10.1007/978-3-662-03223-7_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-08253-5
Online ISBN: 978-3-662-03223-7
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