Multivariate Methods • Discriminant Analysis • Technical Details for the Discriminant Analysis Platform • Description of the Wide Linear Algorithm
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Description of the Wide Linear Algorithm
Wide Linear discriminant analysis is performed as follows:
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The data are standardized by subtracting group means and dividing by pooled standard deviations.
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The singular value decomposition is used to obtain a principal component transformation matrix from the set of singular vectors.
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The number of components retained represents a minimum of 0.9999 of the sum of the squared singular values.
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A linear discriminant analysis is performed on the transformed data, where the data are not shifted by group means. This is a fast calculation because the pooled-within covariance matrix is diagonal.

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Help created on 7/12/2018