GFIT - generalized quadratic approximation of functions under constraints

Published: 1 January 1989| Version 1 | DOI: 10.17632/yk6mhshyd4.1
V.B. Zlokazov


Abstract A method and a program are described for the minimization of a function of the type Σ[inx(x){y(x) - f(x, p)} ^2 , where f(x, p) is a regression, non-linear with respect to the parameter p, and satisfying some additional condition, given by a constraint r(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 filter... Title of program: GFIT Catalogue Id: ABHX_v1_0 Nature of problem The program is intended to extract components from the functions using techniques of the weighted least-squares fitting. The field of applications is the decomposition or filteration of the experimental distributions. Versions of this program held in the CPC repository in Mendeley Data ABHX_v1_0; GFIT; 10.1016/0010-4655(89)90097-0 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)



Computational Physics, Computational Method