PLSRfit: Partial Least Squares Regression (PLSR)

View source: R/PLSRfit.R

PLSRfitR Documentation

Partial Least Squares Regression (PLSR)

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.


MultBiplotR documentation built on Nov. 21, 2023, 5:08 p.m.