Rank Selection for Non-Negative Matrix Factorization R package DBNMFrank version 0.1.0 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. Software Imports: NMF,pmledecon(>= 0.2.0) Yun Cai <Yun.Cai@dal.ca> Comprehensive R Archive Network (CRAN) Yun Cai [aut, cre], Hong Gu [aut], Tobias Kenney [aut] GPL (>= 3) 2022-06-03 application/tgz https://CRAN.R-project.org/package=DBNMFrank doi:10.32614/CRAN.package.DBNMFrank