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vrnmf  

Volume-Regularized Structured Matrix Factorization
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("vrnmf", "1.0.2")



Attach the package and use:
library("vrnmf")
Maintained by
Evan Biederstedt
[Scholar Profile | Author Map]
First Published: 2021-08-20
Latest Update: 2022-02-25
Description:
Implements a set of routines to perform structured matrix factorization with minimum volume constraints. The NMF procedure decomposes a matrix X into a product C * D. Given conditions such that the matrix C is non-negative and has sufficiently spread columns, then volume minimization of a matrix D delivers a correct and unique, up to a scale and permutation, solution (C, D). This package provides both an implementation of volume-regularized NMF and "anchor-free" NMF, whereby the standard NMF problem is reformulated in the covariance domain. This algorithm was applied in Vladimir B. Seplyarskiy Ruslan A. Soldatov, et al. "Population sequencing data reveal a compendium of mutational processes in the human germ line". Science, 12 Aug 2021. <doi:10.1126/science.aba7408>. This package interacts with data available through the 'simulatedNMF' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/vrnmf>. The size of the 'simulatedNMF' package is approximately 8 MB.
How to cite:
Evan Biederstedt (2021). vrnmf: Volume-Regularized Structured Matrix Factorization. R package version 1.0.2, https://cran.r-project.org/web/packages/vrnmf. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0.0 (2021-08-20 14:40), 1.0.1 (2022-01-14 22:40)
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Complete documentation for vrnmf
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