Description Usage Arguments Examples
View source: R/radial_bridge.R
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components.https://en.wikipedia.org/wiki/Principal_component_analysis
1 |
x |
a |
... |
arguments passed to |
correctionA |
identify PCA alignment error type A and make correction is_errorA |
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