NDLI: Non-linear least-squares fitting with microsoft excel solver and related routines in HPLC modelling of retention : I. Considerations of the problems of the method

Content Provider	Springer Nature Link
Author	Nikitas, P. Pappa Louisi, A.
Copyright Year	2000
Abstract	Two problems related to non-linear regression, the evaluation of the best set of fitting parameters and the reliability of the methods used for the estimation of the standard errors of these parameters, are examined. It is shown that a non-linear curve fitting routine, like the Microsoft Excel Solver, may give more than one solution for the same data set and a simple Monte Carlo routine is described for the evaluation of the bestfit. For standard errors, the reliability of two procedures based on the conventional curvature matrix method, four Jackknife techniques and the bootstrap method are examined by comparing their results to those obtained from a Monte Carlo simulation of the experimental data. It is shown that a fitting parameter may follow a nonnormal distribution when the equation to be fitted is complicated, even if the errors on the data are normally distributed. In this case only Monte Carlo methods of data simulation can give accurate information about the standard errors and the confidence intervals of these parameters.
Starting Page	477
Ending Page	486
Page Count	10
File Format	PDF
ISSN	00095893
Journal	Chromatographia
Volume Number	52
Issue Number	7-8
e-ISSN	16121112
Language	English
Publisher	Vieweg Verlag
Publisher Date	2000-01-01
Publisher Place	Wiesbaden
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Column liquid chromatography Non-linear least squares routines Standard errors in fitting parameters Jacknife technique Monte Carlo simulations Analytical Chemistry Organic Chemistry Pharmacy Biochemistry Plant Sciences Measurement Science, Instrumentation
Content Type	Text
Resource Type	Article
Subject	Organic Chemistry Analytical Chemistry Biochemistry Clinical Biochemistry

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