Introduction to statistical, algorithmic and theoretical basis of principal components analysis
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So far we have not discussed the theoretical basis of principal component analysis (PCA). It is not the aim of these articles to delve too far into algorithms or statistical theory. For the algorithmically inclined, the two most common are NIPALS and singular value decomposition (svd) about which there are numerous articles providing technical computational details. We illustrate these articles using NIPALS, but for readers, when you use a software package, please be aware of which method has been employed and it is worth being aware of the main differences.
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