Abstract
Minimization of the weighted nonlinear sum of squares of differences may be converted to the minimization of sum of squares. The Gauss-Newton method is recalled and the length of the step of the steepest descent method is determined by substituting the steepest descent direction in the Gauss-Newton formula. The existence of minimum is shown.
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References
Dennis, J. E. and Schnabel, R. B., Numerical Methods for Unconstrained Optimization and Nonlinear Equations, 1983, Prentice-Hall Inc, Englewoods Cliffs, New Jersey.
Fletcher, R., Practical Methods of Optimization, (2nd ed.), John Wiley and Sons, 1963, (reprinted 1997).
Levenberg, K., A Method for the Solution of Certain Non-linear Problems, Quarterly Journal of Applied Mathematics, 2(1944), 164–168.
Marquardt, D.W., An Algorithm for Least-Squares Estimation of Nonlinear Parameters, Journal of the Society for Industrial and Applied Mathematics, 2(1963), 431–441.
Nagel, G. and Wolff, W., Ein Verfahren zur Minimierung Einer Quadratsumme Nichtlinearer Funktionen, Biometrische Zeitschrift, 16(1974), 431–439.
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Bukac, J. Weighted nonlinear regression. Anal. Theory Appl. 24, 330–335 (2008). https://doi.org/10.1007/s10496-008-0330-y
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DOI: https://doi.org/10.1007/s10496-008-0330-y