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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 (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>.

Versions across snapshots

VersionRepositoryFileSize
0.6.7 rolling linux/jammy R-4.5 nmfkc_0.6.7.tar.gz 717.9 KiB
0.6.7 rolling linux/noble R-4.5 nmfkc_0.6.7.tar.gz 717.9 KiB
0.6.7 rolling source/ R- nmfkc_0.6.7.tar.gz 320.8 KiB
0.6.7 latest linux/jammy R-4.5 nmfkc_0.6.7.tar.gz 717.9 KiB
0.6.7 latest linux/noble R-4.5 nmfkc_0.6.7.tar.gz 717.9 KiB
0.6.7 latest source/ R- nmfkc_0.6.7.tar.gz 320.8 KiB
0.6.7 2026-04-26 source/ R- nmfkc_0.6.7.tar.gz 320.8 KiB
0.6.7 2026-04-23 source/ R- nmfkc_0.6.7.tar.gz 320.8 KiB

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