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Alternating least squares is often used to resolve components contributing to data with a bilinear structure; the basic technique may be extended to alternating constrained least squares. Commonly applied constraints include unimodality, nonnegativity, and normalization of components. Several data matrices may be decomposed simultaneously by assuming that one of the two matrices in the bilinear decomposition is shared between datasets.
Package details 


Author  Katharine M. Mullen 
Maintainer  Katharine Mullen <mullenkate@gmail.com> 
License  GPL (>= 2) 
Version  0.0.6 
Package repository  View on CRAN 
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