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An Organizing Principle For Dynamic Estimation

Author

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  • KALABA, R.
  • TESFATSION, L.

Abstract

This study develops a general multicriteria Flexible Least Squares (FLS) framework for the sequential estimation of process states. Three well-known state estimation algorithms (the Viterbi, Larson-Peschon, and Kalman filters) are derived as monocriterion specializations. The FLS framework is used to clarify both Bayesian and classical statistical procedures for treating potential model specification errors. Recently developed bicriteria specializations (FLS-TVLR, GFLS-ALS), explicitly designed to take model specification errors into account, are also reviewed. The latter specializations concretely demonstrate how the FLS framework can be used to construct estimation algorithms capable of handling disparate sources of information coherently and systematically, without forced scalarization. Annotated pointers to related work can be accessed here: http://www2.econ.iastate.edu/tesfatsi/flshome.htm
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Kalaba, R. & Tesfatsion, L., 1988. "An Organizing Principle For Dynamic Estimation," Papers m8818, Southern California - Department of Economics.
  • Handle: RePEc:fth:socaec:m8818
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    Cited by:

    1. Kalaba, Robert & Tesfatsion, Leigh, 1996. "A multicriteria approach to model specification and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 21(2), pages 193-214, February.
    2. Claudio Morana, 2009. "Realized betas and the cross-section of expected returns," Applied Financial Economics, Taylor & Francis Journals, vol. 19(17), pages 1371-1381.
    3. Kuethe, Todd H. & Foster, Kenneth A. & Florax, Raymond J.G.M., 2008. "A Spatial Hedonic Model with Time-Varying Parameters: A New Method Using Flexible Least Squares," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6306, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Claudio Morana, 2009. "An omnibus noise filter," Computational Statistics, Springer, vol. 24(3), pages 459-479, August.

    More about this item

    Keywords

    econometrics ; evaluation ; linear models;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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