opls_get_all  R Documentation 
Computes orthogonal socres partial least squares (opls_get_all) regressions with the NIPALS algorithm. It retrives a comprehensive set of pls outputs (e.g. vip and sensivity radius). It allows multiple response variables. NOTE: For internal use only!
opls_get_all(X,
Y,
ncomp,
scale,
maxiter,
tol,
algorithm = "pls",
xls_min_w = 3,
xls_max_w = 15)
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 
a list containing the following elements:
ncomp
: the number of components used.
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.
vip
: the projection matrix.
selectivity_ratio
: the matrix of selectivity ratio (see Rajalahti, Tarja, et al. 2009).
Y
: the Y
input.
variance
: a list
conating two objects: x_var
and y_var
.
These objects contain information on the explained variance for the X
and Y
matrices respectively.
transf
: a list
conating two objects: Xcenter
and Xscale
.
weights
: the matrix of wheights.
Leonardo RamirezLopez
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