DBNMFrank: Rank Selection for Non-Negative Matrix Factorization

Given the non-negative data and its distribution, the package estimates the rank parameter for Non-negative Matrix Factorization. The method is based on hypothesis testing, using a deconvolved bootstrap distribution to assess the significance level accurately despite the large amount of optimization error. The distribution of the non-negative data can be either Normal distributed or Poisson distributed.

Version:	0.1.0
Imports:	NMF, pmledecon (≥ 0.2.0)
Published:	2022-06-03
Author:	Yun Cai [aut, cre], Hong Gu [aut], Tobias Kenney [aut]
Maintainer:	Yun Cai <Yun.Cai at dal.ca>
License:	GPL (≥ 3)
NeedsCompilation:	no
CRAN checks:	DBNMFrank results

Documentation:

Reference manual:

DBNMFrank.pdf

Downloads:

Package source:	DBNMFrank_0.1.0.tar.gz
Windows binaries:	r-devel: DBNMFrank_0.1.0.zip, r-release: DBNMFrank_0.1.0.zip, r-oldrel: DBNMFrank_0.1.0.zip
macOS binaries:	r-release (arm64): DBNMFrank_0.1.0.tgz, r-oldrel (arm64): DBNMFrank_0.1.0.tgz, r-release (x86_64): DBNMFrank_0.1.0.tgz, r-oldrel (x86_64): DBNMFrank_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=DBNMFrank to link to this page.