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

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  • Tesfatsion, Leigh

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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File URL: http://www.econ.iastate.edu/tesfatsi/nasahome.htm
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Bibliographic 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: 01 Jan 1991
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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
Phone: +1 515.294.6741
Fax: +1 515.294.0221
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Web page: http://www.econ.iastate.edu
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Related research

Keywords: Automatic evaluation; higher-order partial derivatives; FEED; automated sensitivity analysis;

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Cited by:
  1. Koesrindartoto, Deddy P. & Sun, Junjie & Tesfatsion, Leigh, 2005. "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs," Staff General Research Papers 12388, Iowa State University, Department of Economics.
  2. Max E. Jerrell, . "Automatic Differentiation and Interval Arithmetic for Estimation of Disequilibrium Models," Computing in Economics and Finance 1996 _028, Society for Computational Economics.
  3. 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.

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