plsda_loading: Partial least squares discriminant analysis (PLS-DA) loading

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

Partial least squares discriminant analysis (PLS-DA) loading

Description

This function computes partial least squares discriminant analysis (PLS-DA) loading from the result of the 'pls_da' function.

Usage

plsda_loading(plsda)

Arguments

plsda

The following variables (P,T) are included in the plsda object. P: A matrix containing the PLS-DA loadings for each explanatory variable in the columns, before transformation. T : A matrix with PLS-DA score for explanatory variable in each column

Details

The PLS-DA loading and the p-value by statistical hypothesis testing is added to the pls object returned by the 'pls_da' function in this package.

Value

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

R : PLS-DA loading (Correlation coefficient between PLS-DA score of explanatory variable and each variables in data matrix.)

p.value : p-value of PLS-DA loading

Author(s)

Hiroyuki Yamamoto

References

Yamamoto, H. et al., Dimensionality reduction for metabolome data using PCA, PLS, OPLS, and RFDA with differential penalties to latent variables", Chemom. Intell. Lab. Syst., 98 (2009)

Examples

data(whhl)
X <- whhl$X$liver
Y <- whhl$Y
plsda <- pls_da(X,Y,2)

plsda <- plsda_loading(plsda)

plsda$loading$R
plsda$loading$p.value

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