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Publication Detail
Back to basics: Multivariate qualitative analysis, canonical variates analysis
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Review
  • Authors:
    Davies AMC, Fearn T
  • Publication date:
    01/08/2008
  • Pagination:
    18, 20
  • Journal:
    Spectroscopy Europe
  • Volume:
    20
  • Issue:
    4
  • Status:
    Published
  • Print ISSN:
    0966-0941
Abstract
A study was conducted to assess the similarities and differences of canonical variate analysis with the PCA technique such as PCA are not given any information about groups and group membership but CVA is provided with the information. The number of input variables must be less than the number of samples to apply CVA, which presents a difficulty with spectroscopic data that usually has a large number of variables and can be mitigated by discarding the majority of datapoints or to use some form of compression to retain most of the information in the original data. Another difference is that the transformation from original variables to scores in PCA is a simple rotation in which the axes remain orthogonal but in CVA, the angles between the axes and the scaling of the axes changes so that elliptical shape describing within-group variability becomes a circular or spherical shape.
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