The four functions svdcp() ('cp' for column partitioned), svdbip() or svdbip2() ('bip' for bipartitioned), and svdbips() ('s' for a simultaneous optimization of a set of 'r' solutions), correspond to a singular value decomposition (SVD) by blocks notion, by supposing each block depending on relative subspaces, rather than on two whole spaces as usual SVD does. The other functions, based on this notion, are relative to two column partitioned data matrices x and y defining two sets of subsets x_i and y_j of variables and amount to estimate a link between x_i and y_j for the pair (x_i, y_j) relatively to the links associated to all the other pairs. These methods were first presented in: Lafosse R. & Hanafi M.,(1997) <https://eudml.org/doc/106424> and Hanafi M. & Lafosse, R. (2001) <https://eudml.org/doc/106494>.
Package details 


Author  Roger Lafosse [aut], Fabio Ashtar Telarico [cre, aut] (<https://orcid.org/0000000287407078>) 
Maintainer  Fabio Ashtar Telarico <FabioAshtar.Telarico@fdv.unilj.si> 
License  GPL (>= 3) 
Version  2.0.0 
URL  https://fatelarico.github.io/BMconcor/ 
Package repository  View on CRAN 
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