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.
- Version0.1.0
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release06/03/2022
Team
Yun Cai
Hong Gu
Show author detailsRolesAuthorTobias Kenney
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- Imports2 packages