fopls: fast 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.
In contrast to codeopls function, this one does not compute unnecessary data for local regressions.
For internal use only!
Usage
fopls(X, Y, ncomp, scale, maxiter, tol)
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 X must be scaled.
maxiter
maximum number of iterations.
tol
limit for convergence of the algorithm in the nipals algorithm.
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.
transf a list conating two objects: Xcenter and Xscale.