opls_gs {resemble} | R Documentation |
orthogonal scores algorithm of partial leat squares (opls)
Description
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!
Usage
opls_gs(Xr,
Yr,
Xu,
ncomp,
scale,
response = FALSE,
reconstruction = TRUE,
similarity = TRUE,
fresponse = TRUE,
algorithm = "pls")
Arguments
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:
|
Value
a list containing the following elements:
ncomp
: the number of components.pred_response
: the response predictions forXu
.rmse_reconstruction
: the rmse of the reconstruction forXu
.score_dissimilarity
: the distance score betweenXr
andXu
.
Author(s)
Leonardo Ramirez-Lopez