Principal Variable Analysis (PVA) (Cumming and Wooff, 2007) selects a subset from a set of the variables such that the variables in the subset are as uncorrelated as possible, in an effort to ensure that all aspects of the variation in the data are covered.
allows passing of arguments to other functions
PVA is the generic function for the
Use methods("PVA") to get all the methods for the PVA generic.
PVA.data.frame is a method for a
PVA.matrix is a method for a
data.frame giving the results of the variable selection.
It will contain the columns
Cumming, J. A. and D. A. Wooff (2007) Dimension reduction via principal variables. Computational Statistics and Data Analysis, 52, 550–565.
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