For a sample size of 15 trials, following the procedure described above for HMCMC fitting, increasing errors in chemical shift once again led to a monotonic increase in MAE in the predicted component concentrations, as seen in Benchmark 1 (Table ). The addition of baseline noise did not result in a larger MAE, as seen in Benchmark 2. For the tests with and without noise, chemical shift errors representative of predictions by ChemDraw ® (ca. 0.4 ppm) resulted in classifying each compound as present or absent in the reaction mixture with accuracies of 64% and 61%, and MAEs of 9% and 10%, respectively. Chemical shift errors representative of predictions by DFT resulted in accuracies of 79% and 77%, and MAEs of 5% for both tests. Chemical shift errors representative of referencing known compounds found in a library of chemical shifts led to accuracies of 97% and MAEs of 1% for both tests. These results indicate that our approach can identify the individual component spectra in a composite spectrum, even when more candidate structures are provided than exist in the composite spectrum.