Predict QTS from PCA decomposition — predict.prcomp

This function predicts the QTS of a new sample from the PCA decomposition of a previous sample.

Usage

# S3 method for prcomp_qts
predict(object, newdata, ...)

object: An object of class prcomp_qts as produced by the prcomp.qts_sample() method.
newdata: An object of class qts or qts_sample specifying a QTS or a sample of QTS. The QTS should be evaluated on the same grid as the one used to fit the PCA model. If the evaluation grids map the same domain but with different sampling frequenciesa, the QTS will be linearly interpolated (in the Lie algebra) to the common grid used to fit the PCA model.
...: Additional arguments. Not used here.

An object of class qts_sample containing the predicted QTS.

# Fit PCA model
pr <- prcomp(vespa64$igp, M = 5)
#> ℹ The maximum number of principal component is 63.

# Predict QTS
new_qts <- predict(pr)