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CV-ANOVA for significance testing of PLS and OPLS~R models

机译:CV-ANOVA用于PLS和OPLS〜R模型的重要性测试

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This report describes significance testing for PLS and OPLS~R (orthogonal PLS) models. The testing is applicable to single-Y cases and is based on ANOVA of the cross-validated residuals (CV-ANOVA). Two variants of the CV-ANOVA are introduced. The first is based on the cross-validated predictive residuals of the PLS or OPLS model while the second works with the cross-validated predictive score values of the OPLS model. The two CV-ANOVA diagnostics are shown to work well in those cases where PLS and OPLS work well, that is, for data with many and correlated variables, missing data, etc. The utility of the CV-ANOVA diagnostic is demonstrated using three datasets related to (i) the monitoring of an industrial de-inking process; (ii) a pharmaceutical QSAR problem and (iii) a multivariate calibration application from a sugar refinery.
机译:本报告介绍了针对PLS和OPLS_R(正交PLS)模型的重要性测试。该测试适用于单Y情况,并基于交叉验证残差(CV-ANOVA)的ANOVA。介绍了CV-ANOVA的两个变体。第一种基于交叉验证的PLS或OPLS模型的预测残差,而第二种基于交叉验证的OPLS模型的预测得分值。已显示这两种CV-ANOVA诊断程序在PLS和OPLS正常运行的情况下也能很好地工作,也就是说,对于具有许多相关变量的数据,缺少数据等的情况。使用三个数据集演示了CV-ANOVA诊断程序的实用性与(i)监测工业脱墨过程有关; (ii)药品QSAR问题和(iii)糖厂的多元校准应用程序。

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