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. For internal use only!

Usage

opls(X, Y, ncomp, scale, 
     maxiter, tol, 
     regression = TRUE, 
     pcSelmethod = "cumvar", 
     pcSelvalue = 0.99)

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.

regression

a logical indicating if the function is being used for regression. Otherwise it is used only for projection. Default is TRUE.

pcSelmethod

if regression = TRUE, the method for selecting the number of components. Options are: 'cumvar' (for selecting the number of principal components based on a given cumulative amount of explained variance) and "var" (for selecting the number of principal components based on a given amount of explained variance). Default is 'cumvar'

pcSelvalue

a numerical value that complements the selected method (pcSelmethod). If "cumvar" is chosen, it must be a value (higher than 0 and lower than 1) indicating the maximum amount of cumulative variance that the retained components should explain. If "var" is chosen, it must be a value (higher than 0 and lower than 1) indicating that components that explain (individually) a variance lower than this threshold must be excluded. If "manual" is chosen, it must be a value specifying the desired number of principal components to retain. Default is 0.99.

Value

a list containing the following elements:

Author(s)

Leonardo Ramirez-Lopez


[Package resemble version 1.2.2 Index]