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Results tagged with pca
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user 27187
Principal component analysis (PCA) is a linear dimensionality reduction technique. It reduces a multivariate dataset to a smaller set of constructed variables preserving as much information (as much variance) as possible. These variables, called principal components, are linear combinations of the input variables.
16
votes
Can I do a PCA on repeated measures for data reduction?
UPDATE:
To elaborate, Leann was proposing – however long ago – to conduct a PCA on a dataset with repeated measures. … To run a PCA on the three matrices simultaneously, she would have to 'row bind' the three matrices (e.g. PCA(rbind(X1, X2, X3))). …
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