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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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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