PLSRfit: Partial Least Squares Regression (PLSR)

In villardon/MultBiplotR: Multivariate Analysis Using Biplots in R

Description

Fits a Partial Least Squares Regression (PLSR) to two continuous data matrices

Usage

PLSRfit(Y, X, S = 2, tolerance = 5e-06,
maxiter = 100, show = FALSE)

Arguments

Y	The matrix of dependent variables
X	The Matrix of Independent Variables
S	Dimension of the solution. The default is 2
tolerance	Tolerance for the algorithm.
maxiter	Maximum number of iterations for the algorithm.
show	Logical. Should the calculation process be shown on the screen

Details

Fits a Partial Least Squares Regression (PLSR) to a set of two continuous data matrices

Value

An object of class "PLSR"

Method	PLSR1
X	Independent Variables
Y	Dependent Variables
center	Are data centered?
scale	Are data scaled?
ScaledX	Scaled Independent Variables
ScaledY	Scaled Dependent Variables
XScores	Scores for the Independent Variables
XWeights	Weights for the Independent Variables - coefficients of the linear combination
XLoadings	Factor loadings for the Independent Variables
YScores	Scores for the Dependent Variables
YWeights	Weights for the Dependent Variables - coefficients of the linear combination
YLoadings	Factor loadings for the Dependent Variables
XStructure	Structure Correlations for the Independent Variables
YStructure	Structure Correlations for the Dependent Variables
YXStructure	Structure Correlations two groups

Author(s)

Jose Luis Vicente Villardon

References

Wold, S., Sjöström, M., & Eriksson, L. (2001). PLS-regression: a basic tool of chemometrics. Chemometrics and intelligent laboratory systems, 58(2), 109-130.

villardon/MultBiplotR documentation built on June 5, 2021, 8:55 a.m.