A Comparison of Parametric Approximation Techniques to Continuous-Time Stochastic Dynamic Programming Problems
We compare three parametric techniques to approximate Hamilton-Jacobi-Bellman equations via unidimensional and multidimensional problems. The linear programming technique is very efficient for unidimensional problems and offers a balance of speed and accuracy for multidimensional problems. A comparable projection technique is shown to be slow, but has stable accuracy, whereas a perturbation technique has the least accuracy although its speed suffers least from the curse of dimensionality. The linear programming technique is also shown to be suitable for problems in resource management, including applications to biosecurity and marine reserve design.
|Date of creation:||Sep 2010|
|Date of revision:|
|Contact details of provider:|| Postal: Crawford Building, Lennox Crossing, Building #132, Canberra ACT 2601|
Phone: +61 2 6125 4705
Fax: +61 2 6125 5448
Web page: http://www.crawford.anu.edu.au/research_units/eerh/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, December.
When requesting a correction, please mention this item's handle: RePEc:ags:eerhrr:95044. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search)
If references are entirely missing, you can add them using this form.