multiblock (version 0.8.0)

disco: Distinctive and Common Components with SCA - DISCO

Description

This is a wrapper for the RegularizedSCA::DISCOsca function for computing DISCO.

Usage

disco(X, ncomp = 2, ...)

Arguments

X

list of input blocks.

ncomp

integer number of components to extract.

...

additional arguments (not used).

Value

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

Details

DISCO is a restriction of SCA where Alternating Least Squares is used for estimation of loadings and scores. The loadings (in variable linked mode) are filled with zeros for each iteration in a pattern forcing distinct, local and common components. When used in sample linked mode and only selecting distinct components, it shares a resemblance to SO-PLS, only in an unsupervised setting.

References

Schouteden, M., Van Deun, K., Wilderjans, T. F., & Van Mechelen, I. (2014). Performing DISCO-SCA to search for distinctive and common information in linked data. Behavior research methods, 46(2), 576-587.

See Also

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

Examples

# NOT RUN {
data(potato)
potList <- as.list(potato[c(1,2,9)])
pot.disco  <- disco(potList)
plot(scores(pot.disco), labels="names")

# }