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Optimal control in nonlinear models: a generalised Gauss-Newton algorithm with analytic derivatives

  • Richard Pierse

    (University of Surrey)

In this paper we propose an algorithm for the solution of optimal control problems with nonlinear models based on a generalised Gauss- Newton algorithm but making use of analytic model derivatives. The method is implemented in WinSolve, a general nonlinear model solu- tion program.

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File URL: http://www.fahs.surrey.ac.uk/economics/discussion_papers/2006/DP09-06.pdf
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Paper provided by School of Economics, University of Surrey in its series School of Economics Discussion Papers with number 0906.

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Length: 11 pages
Date of creation: Mar 2006
Date of revision:
Handle: RePEc:sur:surrec:0906
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Web page: http://www.surrey.ac.uk/economics/
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  1. Armstrong, John & Black, Richard & Laxton, Douglas & Rose, David, 1998. "A robust method for simulating forward-looking models," Journal of Economic Dynamics and Control, Elsevier, vol. 22(4), pages 489-501, April.
  2. Boucekkine, Raouf, 1995. "An alternative methodology for solving nonlinear forward-looking models," Journal of Economic Dynamics and Control, Elsevier, vol. 19(4), pages 711-734, May.
  3. Juillard, Michel & Laxton, Douglas & McAdam, Peter & Pioro, Hope, 1998. "An algorithm competition: First-order iterations versus Newton-based techniques," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1291-1318, August.
  4. Juillard, Michel, 1996. "Dynare : a program for the resolution and simulation of dynamic models with forward variables through the use of a relaxation algorithm," CEPREMAP Working Papers (Couverture Orange) 9602, CEPREMAP.
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