Functional Principal Least Squares¶
Partial Least Squares using SVD
moduleauthor:: J. Derek Tucker <jdtuck@sandia.gov>
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fPLS.
pls_svd
(time, qf, qg, no, alpha=0.0)[source]¶ This function computes the partial least squares using SVD
Parameters: - time – vector describing time samples
- qf – numpy ndarray of shape (M,N) of N functions with M samples
- qg – numpy ndarray of shape (M,N) of N functions with M samples
- no – number of components
- alpha – amount of smoothing (Default = 0.0 i.e., none)
Return type: numpy ndarray
Return wqf: f weight function
Return wqg: g weight function
Return alpha: smoothing value
Return values: singular values