A two-dimensional search for a Gauss-Newton algorithm

A.B. Forbes, M. Bartholomew-Biggs

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    This paper describes a fall-back procedure for use with the Gauss-Newton method for nonlinear least-squares problems. While the basic Gauss-Newton algorithm is often successful, it is well-known that it can sometimes generate poor search directions and exhibit slow convergence. For dealing with such situations we suggest a new two-dimensional search strategy. Numerical experiments indicate that the proposed technique can be effective.
    Original languageEnglish
    Pages (from-to)435-447
    JournalAdvanced Modeling and Optimization
    Issue number4
    Publication statusPublished - 2009


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