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
DOI: 10.32614/CRAN.package.DBNMFrank
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


Reference manual: DBNMFrank.pdf


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


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