The application of iterative optimization techniques to chemical kinetic data of large random error

The possibilities of improving the computational processing of chemical rate measurements, in the frame of linear and non-linear least-square fit methods, are investigated. A simple scaling technique to avoid the distortion of the fitted parameters, inherent in the logarithmic transformation of the rate equation, is tested on several examples, and an iterative discarding method for the selection of accurate data points is recommended.