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Two problems encountered in the analysis of progress curves are examined: 1. Systematic deviations due to errors in the initial solute concentrations make the least-squares method unsuitable. The improvements accomplished by the introduction of a proper weighting matrix are investigated. 2. Non-linear parameter optimization implies a dependence of the optimized parameters on their initial estimates, due to the existence of multiple minima. It is shown that the sensitivity of the optimized parameters on the initial estimates is reduced by fitting the slopes of the progress curves. A subsequent fit of the original progress curve data is recommended for refinement of the parameters.
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