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• W2780068737 abstract "Multivariate curve resolution-alternating least-squares (MCR-ALS) is the model of choice when dealing with some non-trilinear arrays, specifically when the data are of chromatographic origin. To drive the iterative procedure to chemically interpretable solutions, the use of constraints becomes essential. In this work, both simulated and experimental data have been analyzed by MCR-ALS, applying chemically reasonable constraints, and investigating the relationship between selectivity, analytical sensitivity (γ) and root mean square error of prediction (RMSEP). As the selectivity in the instrumental modes decreases, the estimated values for γ did not fully represent the predictive model capabilities, judged from the obtained RMSEP values. Since the available sensitivity expressions have been developed by error propagation theory in unconstrained systems, there is a need of developing new expressions or analytical indicators. They should not only consider the specific profiles retrieved by MCR-ALS, but also the constraints under which the latter ones have been obtained." @default.
• W2780068737 created "2018-01-05" @default.
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• W2780068737 date "2018-03-01" @default.
• W2780068737 modified "2023-10-17" @default.
• W2780068737 title "The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares" @default.
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• W2780068737 doi "https://doi.org/10.1016/j.aca.2017.12.008" @default.
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