jive: Joint and Individual Variation Explained - JIVE

In multiblock: Multiblock Data Fusion in Statistics and Machine Learning

Joint and Individual Variation Explained - JIVE

Description

This is a wrapper for the r.jive::jive function for computing JIVE.

Usage

jive(X, ...)

Arguments

X	list of input blocks.
...	additional arguments for r.jive::jive.

Details

Jive performs a decomposition of the variation in two or more blocks into low-dimensional representations of individual and joint variation plus residual variation.

Value

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

References

Lock, E., Hoadley, K., Marron, J., and Nobel, A. (2013) Joint and individual variation explained (JIVE) for integrated analysis of multiple data types. Ann Appl Stat, 7 (1), 523–542.

See Also

Overviews of available methods, multiblock, and methods organised by main structure: basic, unsupervised, asca, supervised and complex.

Examples

 # Too time consuming for testing
  data(candies)
  candyList <- lapply(1:nlevels(candies$candy),function(x)candies$assessment[candies$candy==x,])
  can.jive  <- jive(candyList)
  summary(can.jive)

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