## nsprcomp: Non-Negative and Sparse PCA

This package implements two methods for performing a constrained
principal component analysis (PCA), where non-negativity and/or sparsity
constraints are enforced on the principal axes (PAs). The function
'nsprcomp' computes one principal component (PC) after the other. Each PA
is optimized such that the corresponding PC has maximum additional variance
not explained by the previous components. In contrast, the function
'nscumcomp' jointly computes all PCs such that the cumulative variance is
maximal. Both functions have the same interface as the 'prcomp' function
from the 'stats' package (plus some extra parameters), and both return the
result of the analysis as an object of class 'nsprcomp', which inherits
from 'prcomp'.

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