nmfkc: Non-Negative Matrix Factorization with Kernel Covariates
Performs Non-negative Matrix Factorization (NMF)
with Kernel Covariates. Given an observation matrix and kernel
covariates, it optimizes both a basis matrix and a parameter matrix.
Notably, if the kernel matrix is an identity matrix, the method
simplifies to standard NMF. Also provides NMF with Random Effects
(NMF-RE) via nmfre(), which estimates a mixed-effects model combining
covariate-driven scores with unit-specific random effects together
with wild bootstrap inference, and NMF-based Structural Equation
Modeling (NMF-SEM) via nmf.sem(), which fits a two-block input-output
model for blind source separation and path analysis.
References: Satoh (2025) <doi:10.48550/arXiv.2403.05359>;
Satoh (2026) <doi:10.1007/s42081-026-00349-x>;
Satoh (2025) <doi:10.48550/arXiv.2512.18250>;
Satoh (2026) <doi:10.48550/arXiv.2603.01468>;
Satoh and Tokuda (2026) <doi:10.48550/arXiv.2607.27474>;
Satoh (2026) <doi:10.1007/s42081-025-00314-0>.
| Version: |
0.9.8 |
| Imports: |
stats, graphics, utils, grDevices |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0), mclust, palmerpenguins, quanteda, vars, DiagrammeR, MASS, nlme, lavaan, ade4 |
| Published: |
2026-09-22 |
| DOI: |
10.32614/CRAN.package.nmfkc |
| Author: |
Kenichi Satoh 
[aut, cre] |
| Maintainer: |
Kenichi Satoh <kenichi-satoh at biwako.shiga-u.ac.jp> |
| BugReports: |
https://github.com/ksatohds/nmfkc/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/ksatohds/nmfkc,
https://ksatohds.github.io/nmfkc/ |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Citation: |
nmfkc citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
nmfkc results |
Documentation:
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