Partial least square differential analysis

An in-depth review of statistical methods for metabonomic data analysis is beyond the scope of this chapter. Briefly, there are a few main approaches to data analysis. Examples of multivariate data analyses include the so-called unsupervised analyses such as PCA, independent component analysis (ICA), and hierarchical clustering analysis (HCA), while partial least square differential analysis (PLS-DA) is... 

Avula, B., Wang, Y.-H., Wang, M., Avonto, C., Zhao, J., Smillie, T.J., Rua, D., Khan, I.A. (2014) Quantitative Determination of Phenolic Compounds by UHPLC-UV-MS and Use of Partial Least-square Discriminant Analysis to Differentiate Chemo-types of ChamoimldChrysanthemum Flower Heads. J. Pharm. Biomed. Anal. 88 278-288. 

Chemometric evaluation methods can be applied to the signal from a single sensor by feeding the whole data set into an evaluation program [133,135]. Both principle component analysis (PCA) and partial least square (PLS) models were used to evaluate the data. These are chemometric methods that may be used for extracting information from a multivariate data set (e.g., from sensor arrays) [135]. The PCA analysis shows that the MISiC-FET sensor differentiates very well between different lambda values in both lean gas mixtures (excess air) and rich gas mixtures (excess fuel). The MISiC-FET sensor is seen to behave as a linear lambda sensor [133]. It... 

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