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A synopsis of the smoothing formulae associated with the Kalman Filter

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  • Merkus, H.R.

    (Vrije Universiteit Amsterdam, Faculteit der Economische Wetenschappen en Econometrie (Free University Amsterdam, Faculty of Economics Sciences, Business Administration and Economitrics)

  • Pollock, D.S.G.
  • Vos, A.F.

Abstract

This paper provides straightforward derivations of a wide variety of smoothing formulae which are associated with the Kalman filter. The smoothing operations are of perennial interest in the fields of communications engineering and signal processing. Recently they have begun to interest statisticians and economists. It is often asserted that it is tedious and difficult to derive the formulae. We show that this need not be so. Citation Copyright 1993 by Kluwer Academic Publishers.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Merkus, H.R. & Pollock, D.S.G. & Vos, A.F., 1991. "A synopsis of the smoothing formulae associated with the Kalman Filter," Serie Research Memoranda 0079, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    • Handle: RePEc:vua:wpaper:1991-79
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    Cited by:

    1. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.
    2. González, P. & Idais, H. & Pasadas, M. & Yasin, M., 2019. "3D fuzzy data approximation by fuzzy smoothing bicubic splines," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 164(C), pages 94-102.

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