scholarly journals LSQFT: a nonlinear least squares data fitting subroutine suitable for minicomputers. [In FORTRAN for Hewlett Packard 1000]

1980 ◽  
Author(s):  
W.D. Drotning
Keyword(s):  
Least Squares ◽  
Nonlinear Least Squares ◽  
Data Fitting ◽  
Hewlett Packard

Nonlinear least-squares data fitting in Excel spreadsheets

2010 ◽  
Vol 5 (2) ◽  
pp. 267-281 ◽  
Author(s):  
Gerdi Kemmer ◽  
Sandro Keller
Keyword(s):  
Least Squares ◽  
Nonlinear Least Squares ◽  
Data Fitting ◽  
Fitting In

Powell’s method-based nonlinear least-squares data fitting for the Mittag-Leffler relaxation function

2015 ◽  
Vol 22 (5) ◽  
pp. 1058-1067
Author(s):  
Changqing Fang ◽  
Huiyu Sun ◽  
Jianping Gu
Keyword(s):  
Parameter Estimation ◽  
Least Squares ◽  
Relaxation Function ◽  
Nonlinear Least Squares ◽  
Data Fitting ◽  
Direct Search ◽  
Search Method ◽  
Direct Search Method ◽  
Viscoelastic Models

The Mittag-Leffler relaxation function, [Formula: see text], with [Formula: see text], plays an important role in the fractional viscoelastic models. The Mittag-Leffler function is an infinite series whose analytic derivatives are unexplored, thus a direct search method based on Powell’s method is introduced to solve the minimization problem of nonlinear least-squares data fitting for Mittag-Leffler relaxation function in this paper. A simple and effective method is provided for the determination of the initial values and an acceleration strategy is proposed for this direct search method. Numerical results show this direct search method is efficient in the parameter estimation of the Mittag-Leffler relaxation function. Furthermore, the acceleration strategy proves to be conducive to improving the computational efficiency of this direct search method.

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