Abstract
An extension of the previously proposed method [Dimitrov S.D. & Kamenski D.I. (1991) Computers Chem. Engng 15, 657] for unconstrained parameter estimation in models, expressed as the ratio of any linear functions of the unknown parameters, is described. The results from simulated and real data show that the method provides non-local convergence properties. Also, it is superior to the Gauss-Newton and Marquardt algorithms with respect to sensitivity to the initial parameter estimates.
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