Parallel Low-Rank Approximation with Nonnegativity Constraints R package RcppPlanc version 2.0.15 'Rcpp' bindings for 'PLANC', a highly parallel and extensible NMF/NTF (Non-negative Matrix/Tensor Factorization) library. Wraps algorithms described in Kannan et. al (2018) <doi:10.1109/TKDE.2017.2767592> and Eswar et. al (2021) <doi:10.1145/3432185>. Implements algorithms described in Welch et al. (2019) <doi:10.1016/j.cell.2019.05.006>, Gao et al. (2021) <doi:10.1038/s41587-021-00867-x>, and Kriebel & Welch (2022) <doi:10.1038/s41467-022-28431-4>. Software Depends: R (>= 3.5) Imports: methods, Rcpp, Matrix, hdf5r.Extra LinkingTo: Rcpp, RcppArmadillo, RcppProgress, HighFive Suggests: knitr, withr, rmarkdown, testthat (>= 3.0.0) Andrew Robbins <robbiand@umich.edu> Comprehensive R Archive Network (CRAN) Andrew Robbins [aut, cre] (ORCID: <https://orcid.org/0009-0001-7961-7489>), Yichen Wang [aut], Joshua Welch [cph] (ORCID: <https://orcid.org/0000-0002-5869-2391>), Ramakrishnan Kannan [cph] (ORCID: <https://orcid.org/0000-0002-5852-4806>), Conrad Sanderson [cph] (ORCID: <https://orcid.org/0000-0002-0049-4501>), Blue Brain Project/EPFL [cph] (HighFive Headers), UT-Batelle [cph] (The original PLANC code) GPL (>= 2) 2026-02-26 application/tgz https://CRAN.R-project.org/package=RcppPlanc doi:10.32614/CRAN.package.RcppPlanc