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Gauss–Newton method

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Abstract The Gauss–Newton method for nonlinear regression is described, along with its close relationship with the Fisher scoring method. Its many extensions, sometimes in the form of Fisher scoring, are briefly reviewed, including those for coping with large‐residual problems in nonlinear regression, for optimizing a likelihood or other performance criterion, and for dealing with parameters with constraints. WIREs Comput Stat 2012 doi: 10.1002/wics.1202 This article is categorized under: Algorithms and Computational Methods > Quadratic and Nonlinear Programming Algorithms and Computational Methods > Numerical Methods

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Algorithms and Computational Methods > Quadratic and Nonlinear Programming
Algorithms and Computational Methods > Numerical Methods

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