rcca_loading {loadings}

Regularized canonical correlation analysis (RCCA-DA) loading

Description

This function computes regularized canonical correlation analysis for discriminant analysis (RCCA-DA) loading from the result of the 'rcca_da' function.

Usage

rcca_loading(rcca)

Arguments

rcca

The following variables (Wx,P,T,Wy and S) are included in the rcca object.

Wx : A matrix with RCCA-DA weight for explanatory variable in each column

P: A matrix containing the RCCA-DA loadings for each explanatory variable in the columns, before transformation.

T : A matrix with RCCA-DA score for explanatory variable in each column

Wy : A matrix with RCCA-DA weight for explanatory variable in each column

S : A matrix with RCCA-DA score for response variable in each column

Details

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

Value

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

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

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

Author(s)

Hiroyuki Yamamoto

References

Yamamoto, H. et al., Canonical correlation analysis for multivariate regression and its application to metabolic fingerprinting", Biochem. Eng. Journal, 40 (2008) 199-204.

Examples

data(whhl)
X <- whhl$X$liver
Y <- whhl$Y
rcca <- rcca_da(X,Y,0.5,2)

rcca <- rcca_loading(rcca)

rcca$loading$R
rcca$loading$p.value