hogsvd: Higher Order Generalized SVD - HOGSVD

In multiblock: Multiblock Data Fusion in Statistics and Machine Learning

Higher Order Generalized SVD - HOGSVD

Description

This is a simple implementation for computing HOGSVD

Usage

hogsvd(X)

Arguments

X	list of input blocks.

Details

HOGSVD is a generalisation of SVD to two or more blocks. It finds a common set of loadings across blocks and individual sets of scores per block.

Value

multiblock object including relevant scores and loadings. Relevant plotting functions: multiblock_plots and result functions: multiblock_results.

References

Ponnapalli, S. P., Saunders, M. A., Van Loan, C. F., & Alter, O. (2011). A higher-order generalized singular value decomposition for comparison of global mRNA expression from multiple organisms. PloS one, 6(12), e28072.

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(candies)
candyList <- lapply(1:nlevels(candies$candy),function(x)candies$assessment[candies$candy==x,])
can.hogsvd <- hogsvd(candyList)
scoreplot(can.hogsvd, block=1, labels="names")

multiblock documentation built on Nov. 18, 2023, 5:06 p.m.