Principal Components

Multivariate Analyses

Principal Components

For principal components from a covariance matrix, the names of the variables containing principal component scores are PCV1, PCV2, PCV3, and so on. The output component scores are a linear combination of the centered Y variables with coefficients equal to the eigenvectors of the covariance matrix.

For principal components from a correlation matrix, the names of the variables containing principal component scores are PCR1, PCR2, PCR3, and so on. The output component scores are a linear combination of the standardized Y variables with coefficients equal to the eigenvectors of the correlation matrix.

If you specify Variance=Eigenvalues in the multivariate method options dialog, the new variables of principal component scores have mean zero and variance equal to the associated eigenvalues. If you specify Variance=1, the new variables have variance equal to one.

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