This package implements two methods for performing a constrained principal component analysis (PCA), where nonnegativity 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'.
Package details 


Author  Christian Sigg [aut, cre], R Core team [aut] 
Date of publication  20140717 23:54:11 
Maintainer  Christian Sigg <christian@siggiten.ch> 
License  GPL (>= 2) 
Version  0.5 
URL  http://siggiten.ch/research/ 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.