Why Kalman Filter?

R. D. Snyder

No 267075, Department of Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: In this paper the Kalman filter and regression approaches for estimating linear state space models are compared. It is argued that the Kalman filter is no more efficient from a computational point of view, is relatively more complex and hence more obtruse, and that as consequence its central role in the smoothing, estimation and prediction of time series is questionable.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 13
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Persistent link: https://EconPapers.repec.org/RePEc:ags:monebs:267075

DOI: 10.22004/ag.econ.267075

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