HALSacc                 Accelerated hierarchical alternating least
                        squares NMF. For a reference to the method, see
                        N. Gillis, Nonnegative matrix factorization:
                        complexity, algorithms and applications
                        [Section 4.2, Algo. 6], PhD thesis, Université
                        catholique de Louvain, February 2011.
PGNMF                   NMF by alternating non-negative least squares
                        using projected gradients.  For a reference to
                        the method, see C.-J. Lin, "Projected Gradient
                        Methods for Non-negative Matrix Factorization",
                        Neural computation 19.10 (2007): 2756-2779.
hNMF                    Hierarchical non-negative matrix factorization.
imoverlay               Overlay a mask or a color scaled image on top
                        of a background image
initializeNMF           Initialize NMF model with initial spectral data
initializeSPA           The successive projection algorithm, a useful
                        method for initializing the NMF source matrix
oneLevelNMF             Perform Non-Negative Matrix factorization
preProcesInputData      Condition input data matrix properly for NMF
residualNMF             Computation of relative NMF residual per
                        observation
scaleNMFResult          Apply fixed scaling to NMF model matrices by
                        normalizing the basis vectors
semiNMF                 Semi-NMF based on multiplicative update rules.
                        Reference: C. Ding, T. Li, and M.I. Jordan,
                        "Convex and semi-nonnegative matrix
                        factorizations", IEEE Transations on Pattern
                        Analysis and Machine Intelligence, vol. 32, no.
                        1, pp. 45-55, 2010.
