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, non-negativity, 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.
Changes in version 0.0.6 o Moved examples_chemo.zip within package o Changed function calls to nnls to nnls::nnls()
Changes in version 0.0.5 o Better compression obtained by using R CMD build --resave-data o Added dependence on R 2.10
Changes in version 0.0.4
o Thanks to Jan Gerretzen, a bug that appears when (normS > 0 && normS != 1) is removed.