Abstract
Kalman filter presents a theoretical background for various recursive methods in (linear) systems, particularly in (multivariate) time series models. In general, one speaks on so-called Kalman (or Kalman–Bucy) recursions for filtering, predicting, and smoothing in the framework of so-called state space model; see, e.g., Brockwell and Davis (1993, 1996), Durbin and Koopman (2012), Hamilton (1994), Harvey (1989), and others.
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Cipra, T. (2020). State Space Models of Time Series. In: Time Series in Economics and Finance. Springer, Cham. https://doi.org/10.1007/978-3-030-46347-2_14
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DOI: https://doi.org/10.1007/978-3-030-46347-2_14
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