Functional Principal Least Squares#
Partial Least Squares using SVD
moduleauthor:: J. Derek Tucker <jdtuck@sandia.gov>
- 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