A Unified Approach to Dynamic Estimation

R. Kalaba and Leigh Tesfatsion ()

Staff General Research Papers from Iowa State University, Department of Economics

Abstract: Discrepancies between assumed dynamical models and observations are often handled by making further probabilistic assumptions, a tactic which has both strengths and weaknesses. A re-examination of filtering and smoothing is conducted, and an alternative multicriteria Flexible Least Squares (FLS) approach is advanced that does not require a probabilistic interpretation for discrepancy terms. This approach involves vector minimization as a key ingredient, and it specializes to the well-known Kalman, Viterbi, Larson-Peschon, and Swerling filters. Annotated pointers to related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/flshome.htm

Keywords: nonlinear estimation; flexible least squares; Kalman filtering (search for similar items in EconPapers)
JEL-codes: C1 C5 (search for similar items in EconPapers)
Date: 2004-01-11

Published in Information Sciences, September 1991, Vol. 57-58, pp. 159-171.

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Persistent link: http://EconPapers.repec.org/RePEc:isu:genres:11189

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