Abstract
One of the aims of a principal component analysis (PCA) is to reduce the dimensionality of a collection of observations. If we plot the first two principal components of the observations, it is often the case that one can already detect the main structure of the data. Another aim is to detect atypical observations in a graphical way, by looking at outlying observations on the principal axes.
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© 1996 Physica-Verlag Heidelberg
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Croux, C., Ruiz-Gazen, A. (1996). A Fast Algorithm for Robust Principal Components Based on Projection Pursuit. In: Prat, A. (eds) COMPSTAT. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-46992-3_22
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DOI: https://doi.org/10.1007/978-3-642-46992-3_22
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-0953-4
Online ISBN: 978-3-642-46992-3
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