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GFIT – Generalized quadratic approximation of functions under constraints. (English) Zbl 0798.65018

Summary: A method and a program are described for the minimization of a function of the following type \(\Sigma_ x w(x)\{y(x) - f(x,p)\}^ 2\), where \(f(x,p)\) is a regression, nonlinear with respect to the parameter \(p\), and satisfying some additional condition, given by a constraint \(r(f(x,p)) = 0\). The problem is solved using a special recalculation of the weight function \(w(x)\) so that this constraint is taken into account. The method is the most appropriate and efficient for the solution of problems of decompositional filtering of data (function decomposition, robust regression analysis etc.).

MSC:

65D10 Numerical smoothing, curve fitting
65K05 Numerical mathematical programming methods
65C99 Probabilistic methods, stochastic differential equations
90C20 Quadratic programming
62J02 General nonlinear regression

Software:

GFIT
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Full Text: DOI

References:

[1] Zlokazov, V. B., Preprint of JINR, P10-87-894 (1986), Dubna
[2] Zlokazov, V. B., Preprint of JINR, P10-86-502 (1986), Dubna
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