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Understanding the Kalman Filter: an Object Oriented Programming Perspective

Ralph Snyder () and Catherine Forbes

No 14/99, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: The basic ideals underlying the Kalman filter are outlined in this paper without direct recourse to the complex formulae normally associated with this method. The novel feature of the paper is its reliance on a new algebraic system based on the first two moments of the multivariate normal distribution. The resulting framework lends itself to an object-oriented implementation on computing machines and so many of the ideas are presented in these terms. The paper provides yet another perspective of Kalman filtering, one that many should find relatively easy to understand.

Keywords: Time series analysis; forecasting; Kalman filter; dynamic linear statistical models; object oriented programming. (search for similar items in EconPapers)
JEL-codes: C40 C22 C32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp and nep-ets
Date: 1999-12
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