pls_svd: Partial least squares

In loadings: Loadings for Principal Component Analysis and Partial Least Squares

Partial least squares

Description

This function performs partial least squares. In this function, data matrix for explanatory variable is automatically scaled to zero mean and unit variance (i.e. autoscaling) for each variables.

Usage

pls_svd(X,Y)

Arguments

X	Data matrix of explanatory variables that include variables in each columns.
Y	Dummy matrix that include group information 0,1 in each columns.

Details

This function is wrapper function of "pls_rog" fucntion that the smoothing parameter kappa=0.

Value

The return value is a list object that contains the following elements:

P : A matrix with PLS loading for explanatory variable in each column

T : A matrix with PLS score for explanatory variable in each column

Q : A matrix with PLS loading for response variable in each column

U : A matrix with PLS score for response variable in each column

Author(s)

Hiroyuki Yamamoto

References

Barker, M. and Rayens, W. (2003) Partial Least Squares for Discrimination. Journal of Chemometrics, 17, 166-173.

Examples

data(whhl)
X <- whhl$X$liver
Y <- whhl$Y

pls <- pls_svd(X,Y)

loadings documentation built on May 29, 2024, 8:01 a.m.