title: GGOPT: an unconstrained non-linear optimizer.
abstract: 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.
authors: Center for Bioengineering, University of Washington, Seattle 98195.
authors: J B
authors: JB
authors: Bassingthwaighte
authors: I S
authors: IS
authors: Chan
authors: A A
authors: AA
authors: Goldstein
authors: I B
authors: IB
authors: Russak
mesh_terms: D000465:Algorithms; D001699:Biometry; D012984:Software