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Automatic Evaluation of Higher-Order Partial Derivatives for Nonlocal Sensitivity Analysis

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Author Info
Tesfatsion, Leigh S.

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Abstract

This proceedings paper surveys work on the FEED (Fast Efficient Evaluation of Derivatives) algorithm originally developed by Kalaba, Tesfatsion, and Wang (1983), with particular reference to the use of FEED for the implementation of nonlocal automated sensitivity techniques; see the articles below. The relationship of FEED to the automatic differentiation algorithms developed by other SIAM Workshop participants is clarified. Related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/nasahome.htm

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Publisher Info
Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 11183.

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Date of creation: 11 Jan 2004
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Handle: RePEc:isu:genres:11183

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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
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Related research
Keywords: Automatic evaluation; higher-order partial derivatives; FEED; automated sensitivity analysis;

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Find related papers by JEL classification:
B4 - Schools of Economic Thought and Methodology - - Economic Methodology
C0 - Mathematical and Quantitative Methods - - General

Cited by:
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  1. Max E. Jerrell, 1999. "Environments for Global Optimization Using Interval Arithmetic and Computational (Automatic) Differentiation," Computing in Economics and Finance 1999 1321, Society for Computational Economics. [Downloadable!]
  2. Deddy Koesrindartoto & Junjie Sun, 2005. "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs," Computing in Economics and Finance 2005 50, Society for Computational Economics. [Downloadable!]
    Other versions:
  3. Max E. Jerrell, . "Automatic Differentiation and Interval Arithmetic for Estimation of Disequilibrium Models," Computing in Economics and Finance 1996 _028, Society for Computational Economics. [Downloadable!]
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