Package: DBNMFrank 0.1.0
Yun Cai
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.
Authors:
DBNMFrank_0.1.0.tar.gz
DBNMFrank_0.1.0.tar.gz(r-4.5-noble)DBNMFrank_0.1.0.tar.gz(r-4.4-noble)
DBNMFrank_0.1.0.tgz(r-4.4-emscripten)DBNMFrank_0.1.0.tgz(r-4.3-emscripten)
DBNMFrank.pdf |DBNMFrank.html✨
DBNMFrank/json (API)
# Install 'DBNMFrank' in R: |
install.packages('DBNMFrank', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:fff21cc9f8. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 06 2024 |
R-4.5-linux | OK | Dec 06 2024 |
Exports:DBrank
Dependencies:BiobaseBiocGenericsBiocManagercliclustercodetoolscolorspacedata.tabledigestdoParallelfansifarverforeachgenericsggplot2gluegridBasegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmeNMFpillarpkgconfigplyrpmledeconR6RColorBrewerRcppregistryreshape2rlangrmutilrngtoolsscalessplitstackshapestringistringrtibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
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Rank Selection for Non-Negative Matrix Factorization | DBrank |