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An Overview of Automatic Differentiation

Author

Listed:
  • Jean Utke
  • Paul D Hovland

    () (Mathematics and Computer Science Divisio Argonne National Laboratory)

Abstract

We provide an overview of automatic differentiation (AD), a technique for the efficient computation of derivatives of functions defined in some programming language. We give a short explanation of how AD works, indicate the anticipated cost of derivatives computed using AD, and survey what AD tools are available. We illustrate the flexibility and utility of AD techniques with a maximum likelihood example and survey other possible applications

Suggested Citation

  • Jean Utke & Paul D Hovland, 2005. "An Overview of Automatic Differentiation," Computing in Economics and Finance 2005 149, Society for Computational Economics.
  • Handle: RePEc:sce:scecf5:149
    as

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    More about this item

    JEL classification:

    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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