Successive Bayesian estimation of reaction rate constants from spectral data

The successive estimation of regression parameters is an effective technique applied in nonlinear regression analysis. In the paper, this method is used for obtaining kinetic information from spectral data without any pure component spectra. In order to study the way kinetics may be determined by ‘hard’ model without separate calibration, the simulated example of a two-step reaction was constructed. With the help of real-world example, this approach is compared with known methods of kinetic modelling. All calculations have been performed with the help of new nonlinear regression software, Fitter. Such approach is valuable in case the concentrations of pure components are not available or if ‘soft’ calibration methods are inexact or time consuming.