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Exact Sequential Filtering, Smoothing, and Prediction for Nonlinear Systems

Author

Listed:
  • Kalaba, Robert E.
  • Tesfatsion, Leigh S.

Abstract

This study develops two algorithms for the exact sequential updating of the optimal solution for a general discrete-time nonlinear least squares estimation problem as the process length increases and new observations are obtained. One algorithm proceeds via an imbedding on the process length and the final state vector. The second algorithm proceeds via an imbedding on the process length and the final observation vector. Each algorithm generates optimal (least cost) filtered and smoothed state estimates, together with optimal one-step-ahead state predictions. Annotated pointers to related work can be accessed here: http://www2.econ.iastate.edu/tesfatsi/flshome.htm

Suggested Citation

  • Kalaba, Robert E. & Tesfatsion, Leigh S., 1988. "Exact Sequential Filtering, Smoothing, and Prediction for Nonlinear Systems," Staff General Research Papers Archive 11199, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genres:11199
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    More about this item

    Keywords

    Flexible least squares; nonlinear estimation; smoothness pior; sequential updating;
    All these keywords.

    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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