opls {resemble} | R Documentation |
orthogonal scores algorithn of partial leat squares (opls)
Description
Computes orthogonal socres 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(X,
Y,
ncomp,
scale,
maxiter,
tol,
algorithm = "pls",
xls_min_w = 3,
xls_max_w = 15)
Arguments
X |
a matrix of predictor variables. |
Y |
a matrix of either a single or multiple response variables. |
ncomp |
the number of pls components. |
scale |
logical indicating whether |
maxiter |
maximum number of iterations. |
tol |
limit for convergence of the algorithm in the nipals algorithm. |
algorithm |
(for weights computation) a character string indicating
what method to use. Options are:
|
xls_min_w |
(for weights computation) an integer indicating the minimum window size for the "xls"
method. Only used if |
xls_max_w |
(for weights computation) an integer indicating the maximum window size for the "xls"
method. Only used if |
Value
a list containing the following elements:
coefficients
: the matrix of regression coefficients.bo
: a matrix of one row containing the intercepts for each component.scores
: the matrix of scores.X_loadings
: the matrix of X loadings.Y_loadings
: the matrix of Y loadings.projection_mat
: the projection matrix.Y
: theY
input.transf
: alist
conating two objects:Xcenter
andXscale
.weights
: the matrix of wheights.
Author(s)
Leonardo Ramirez-Lopez