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nmfkc  

Non-Negative Matrix Factorization with Kernel Covariates
View on CRAN: Click here


Download and install nmfkc package within the R console
Install from CRAN:
install.packages("nmfkc")

Install from Github:
library("remotes")
install_github("cran/nmfkc")

Install by package version:
library("remotes")
install_version("nmfkc", "0.6.7")



Attach the package and use:
library("nmfkc")
Maintained by
Kenichi Satoh
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-15
Latest Update: 2026-04-15
Description:
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 (2025) <doi:10.48550/arXiv.2510.10375>; Satoh (2025) <doi:10.48550/arXiv.2512.18250>; Satoh (2026) <doi:10.48550/arXiv.2603.01468>; Satoh (2026) <doi:10.1007/s42081-025-00314-0>.
How to cite:
Kenichi Satoh (2026). nmfkc: Non-Negative Matrix Factorization with Kernel Covariates. R package version 0.6.7, https://cran.r-project.org/web/packages/nmfkc. Accessed 21 Aug. 2026.
Previous versions and publish date:
(2026-07-14 01:50), 0.6.7 (2026-04-15 15:00), 0.7.3 (2026-05-14 01:40), 0.8.2 (2026-06-14 15:50)
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Complete documentation for nmfkc
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