opls_gs  R Documentation 
Computes orthogonal scores partial least squares (opls) regressions with the NIPALS algorithm. It allows multiple response variables. It does not return the variance information of the components. NOTE: For internal use only!
opls_gs(Xr,
Yr,
Xu,
ncomp,
scale,
response = FALSE,
reconstruction = TRUE,
similarity = TRUE,
fresponse = TRUE,
algorithm = "pls")
Xr 
a matrix of predictor variables for the training set. 
Yr 
a matrix of a single response variable for the training set. 
Xu 
a matrix of predictor variables for the test set. 
ncomp 
the number of pls components. 
scale 
logical indicating whether 
response 
logical indicating whether to compute the prediction of 
reconstruction 
logical indicating whether to compute the reconstruction error of 
similarity 
logical indicating whether to compute the the distance score between 
fresponse 
logical indicating whether to compute the score of the variance not explained for 
algorithm 
(for weights computation) a character string indicating
what method to use. Options are:

a list containing the following elements:
ncomp
: the number of components.
pred_response
: the response predictions for Xu
.
rmse_reconstruction
: the rmse of the reconstruction for Xu
.
score_dissimilarity
: the distance score between Xr
and Xu
.
Leonardo RamirezLopez
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