Vertices Principal Component Analysis (V-PCA) and Centers Principal Component Analysis (C-PCA) are variants of Principal Component Analysis (PCA) to deal with two-way interval-valued data. In this case the observation units are represented as hyperrectangles instead of points. Tucker3 and CANDECOMP/PARAFAC are component analysis techniques to analyze the underlying structure of three-way data sets. In the present paper, after recalling the above mentioned methods, we extend the C-PCA and V-PCA methods to deal with three-way interval-valued data by means of Tucker3 and CANDECOMP/PARAFAC and we describe how to represent the observation units in the obtained low-dimensional space. Furthermore, an application of the extended methods-called Three-way Vertices Principal Component Analysis (3V-PCA) and Three-way Centers Principal Component Analysis (3C-PCA)-to three-way interval-valued air pollution data is described. Copyright © 2004 John Wiley & Sons, Ltd.
CITATION STYLE
Giordani, P., & Kiers, H. A. L. (2004). Three-way component analysis of interval-valued data. Journal of Chemometrics, 18(5), 253–264. https://doi.org/10.1002/cem.868
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