After completion of the learning phase (step="sfa") this function can be used to apply the learned function to the input data. The execution is completed in 4 steps: 1. projection on the input principal components (dimensionality reduction) 2. expansion (if necessary) 3. projection on the whitened (expanded) space 4. projection on the slow functions
sfaExecute(sfaList, DATA, prj = NULL, ncomp = NULL)A list that contains all information about the handled sfa-structure
Input data, each column a different variable
If not NULL, the preprocessing step 1 is skipped for SFA2
number of learned functions to be used
matrix DATA containing the calculated output