Abstract
Principal component outlier detection methods are discussed and their application in the soft independent modelling of class analogy (SIMCA) method of pattern recognition is clarified. SIMCA is compared to allocation procedures based on the Mahalanobis distance. Finally, the differences between the SIMCA method and quadratic discriminant analysis are discussed. The discussion is illustrated with an example from spectroscopy.
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