Abstract
The analysis of mixtures is a routine task in the analytical chemistry area as well as in other research fields. The objective is to identify, quantify, and interpret the chemical components of the mixtures. Various bilinear factor decomposition methods, including MCR-ALS, NMFand BNFA, have been proposed to solve this problem. However, there is little knowledge about their comparative performance in terms of different factors, such as solution reliability, calculation speed, convergence, flexibility in constraint implementation, and ease of results interpretation.To address these issues, this work aims to compare these methods using data examples from data simulations, environmental source apportionment studies, and chromatographic analysis of chemical mixtures. Through this comparison, we hope to gain insights into the strengths and weaknesses of each method and provide recommendations for researchers working in this field. This comprehensive comparison will help researchers choose the appropriate method for their specific analysis needs, ultimately leading to more accurate and efficient analysis.
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