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Obtaining Initial Parameter Estimates for Nonlinear Systems Using Multicriteria Associative Memories

Author

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

Abstract

This article appeared in Computer Science in Economics and Management (now Computational Economics). Parameter estimation problems for nonlinear systems are typically formulated as nonlinear optimization problems. For such problems, one has the usual difficulty that standard successive approximation schemes require good initial estimates for the parameter vector. This article develops a simple multicriteria associative memory (MAM) method for obtaining good initial estimates for nonlinear parameter estimation problems. The method is implemented in Fortran by the MAM program. Annotated pointers to related work can be accessed here: http://www2.econ.iastate.edu/tesfatsi/vita.htm#MAM

Suggested Citation

  • Kalaba, Robert E. & Tesfatsion, Leigh S., 1991. "Obtaining Initial Parameter Estimates for Nonlinear Systems Using Multicriteria Associative Memories," Staff General Research Papers Archive 11184, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genres:11184
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    Cited by:

    1. Moore, II, James E. & Kim, Geunyoung & Cho, Seongdil & Hu, Hsi-hwa & Xu, Rong, 1997. "Evaluating System ATMIS Technologies Via Rapid Estimation Of Network Flows: Final Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt5c70f3d9, Institute of Transportation Studies, UC Berkeley.

    More about this item

    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
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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