| Autor: |
Bassingthwaighte, J.B., Chan, I.S., Goldstein, A.A., Russak, I.B. |
| Přispěvatelé: |
Naval Postgraduate School (U.S.), Applied Mathematics |
| Rok vydání: |
2012 |
| Popis: |
Comput Methods Programs Biomed. Author manuscript; available in PMC 2012 Jun 7 GGOPT is a derivative-free non-linear optimizer for smooth functions with added noise. If the function values arise from observations or from extensive computations, these errors can be considerable. GGOPT uses an adjustable mesh together with linear least squares to find smoothed values of the function, gradient and Hessian at the center of the mesh. These values drive a descent method that estimates optimal parameters. The smoothed values usually result in increased accuracy. grant RR 01243 and EB08407 from the National Institutes of Health grant RR 01243 and EB08407 from the National Institutes of Health |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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