This is a wrapper for the RGCCA::rgcca
function for computing IFA.
ifa(X, ncomp = 1, scale = FALSE, verbose = FALSE, ...)
list
of input data blocks.
integer
number of principal components to return.
logical
indicating if variables should be standardised (default=FALSE).
logical
indicating if intermediate results should be printed.
additional arguments to RGCCA::rgcca
.
multiblock
object with associated with printing, scores, loadings. Relevant plotting functions: multiblock_plots
and result functions: multiblock_results
.
IFA rotates two matrices to align one or more factors against each other, maximising correlations.
Tucker, L. R. (1958). An inter-battery method of factor analysis. Psychometrika, 23(2), 111-136.
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.
data(potato)
X <- potato$Chemical
ifa.pot <- ifa(potato[1:2])