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.

中文翻译：

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约束对扩展多元曲线分辨率交替最小二乘法实现的分析品质因数的影响

多元曲线分辨率交替最小二乘法 (MCR-ALS) 是处理某些非三线性阵列时的首选模型，特别是当数据来自色谱法时。为了将迭代过程推向化学可解释的解决方案，约束的使用变得必不可少。在这项工作中，MCR-ALS 对模拟和实验数据进行了分析，应用化学上合理的约束，并研究了选择性、分析灵敏度 (γ) 和预测均方根误差 (RMSEP) 之间的关系。随着仪器模式的选择性降低，从获得的 RMSEP 值判断，γ 的估计值不能完全代表预测模型的能力。由于可用的灵敏度表达式已通过无约束系统中的误差传播理论开发，因此需要开发新的表达式或分析指标。他们不仅应该考虑 MCR-ALS 检索到的特定配置文件，还应该考虑获得后者的约束条件。