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This is a wrapper for the RGCCA::rgcca function for computing IFA.

Usage

ifa(X, ncomp = 1, scale = FALSE, verbose = FALSE, ...)

Arguments

X

list of input data blocks.

ncomp

integer number of principal components to return.

scale

logical indicating if variables should be standardised (default=FALSE).

verbose

logical indicating if intermediate results should be printed.

...

additional arguments to RGCCA::rgcca.

Value

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

Details

IFA rotates two matrices to align one or more factors against each other, maximising correlations.

References

Tucker, L. R. (1958). An inter-battery method of factor analysis. Psychometrika, 23(2), 111-136.

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

ifa.pot  <- ifa(potato[1:2])