Methods for fitting equations with two or more non-linear parameters
- 1 August 1976
- journal article
- research article
- Published by Portland Press Ltd. in Biochemical Journal
- Vol. 157 (2) , 489-492
- https://doi.org/10.1042/bj1570489
Abstract
1. Descriptions are given of two ways for fitting non-linear equations by least-squares criteria to experimental data. One depends on solving a set of non-linear simultaneous equations, and the other on Taylor's theorem. 2. It is shown that better parameter estimates result when an equation with two or more non-linear parameters is fitted to all the sets of data simultaneously than when it is fitted to each set in turn.This publication has 7 references indexed in Scilit:
- A comparison of seven methods for fitting the Michaelis-Menten equationBiochemical Journal, 1975
- Statistical Estimations in Enzyme KineticsEuropean Journal of Biochemistry, 1974
- Use of progress curves to investigate product inhibition in enzyme-catalysed reactions. Application to the soluble mitochondrial adenosine triphosphataseBiochemical Journal, 1973
- A Simple Digital‐Computer Program for Estimating the Parameters of the Hill EquationEuropean Journal of Biochemistry, 1973
- The Statistical Analysis of Enzyme Kinetic DataPublished by Wiley ,1967
- Computer Programmes for Processing Enzyme Kinetic DataNature, 1963
- Statistical estimations in enzyme kineticsBiochemical Journal, 1961