Understanding the Kalman Filter: an Object Oriented Programming Perspective
Ralph Snyder () and
No 14/99, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics
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
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:msh:ebswps:1999-14
Ordering information: This working paper can be ordered from
http://business.mona ... -business-statistics
Access Statistics for this paper
More papers in Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics PO Box 11E, Monash University, Victoria 3800, Australia. Contact information at EDIRC.
Bibliographic data for series maintained by Dr Xibin Zhang ().