Generalised Singular Value Decomposition - GSVD

This is a wrapper for the geigen::gsvd function for computing GSVD.

Usage

gsvd(X)

Arguments

X

list of input data blocks.

Value

multiblock object with associated with printing, scores, loadings. Relevant plotting functions: multiblock_plots and result functions: multiblock_results.

Details

GSVD is a generalisation of SVD to two variable-linked matrices where common loadings and block-wise scores are estimated.

References

Van Loan, C. (1976) Generalizing the singular value decomposition. SIAM Journal on Numerical Analysis, 13, 76–83.

See also

Overviews of available methods, multiblock, and methods organised by main structure: basic, unsupervised, asca, supervised and complex. Common functions for computation and extraction of results and plotting are found in multiblock_results and multiblock_plots, respectively.

Examples

data(potato)
X <- potato$Chemical

gsvd.pot <- gsvd(lapply(potato[3:4], t))