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nsprcomp  

Non-Negative and Sparse PCA
View on CRAN: Click here


Download and install nsprcomp package within the R console
Install from CRAN:
install.packages("nsprcomp")

Install from Github:
library("remotes")
install_github("cran/nsprcomp")

Install by package version:
library("remotes")
install_version("nsprcomp", "0.5.1-2")



Attach the package and use:
library("nsprcomp")
Maintained by
Christian Sigg
[Scholar Profile | Author Map]
First Published: 2013-04-16
Latest Update: 2018-06-05
Description:
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'. See and Sigg et al. (2008) for more details.
How to cite:
Christian Sigg (2013). nsprcomp: Non-Negative and Sparse PCA. R package version 0.5.1-2, https://cran.r-project.org/web/packages/nsprcomp. Accessed 07 Apr. 2025.
Previous versions and publish date:
0.2 (2013-04-16 21:28), 0.3 (2013-05-29 09:07), 0.4.1 (2013-09-22 22:52), 0.4 (2013-09-19 11:57), 0.5 (2014-07-17 23:54)
Other packages that cited nsprcomp R package
View nsprcomp citation profile
Other R packages that nsprcomp depends, imports, suggests or enhances
Complete documentation for nsprcomp
Functions, R codes and Examples using the nsprcomp R package
Some associated functions: asdev . cardinality . nscumcomp . nsprcomp . peav . 
Some associated R codes: asdev.R . cardinality.R . normv.R . nscumcomp.R . nsprcomp.R . peav.R .  Full nsprcomp package functions and examples
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