DBNMFrank
Rank Selection for Non-Negative Matrix Factorization
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | DBNMFrank_0.1.0.tar.gz |
2.9 KiB |
0.1.0 |
rolling linux/noble R-4.5 | DBNMFrank_0.1.0.tar.gz |
2.9 KiB |
0.1.0 |
rolling source/ R- | DBNMFrank_0.1.0.tar.gz |
2.9 KiB |
0.1.0 |
latest linux/jammy R-4.5 | DBNMFrank_0.1.0.tar.gz |
2.9 KiB |
0.1.0 |
latest linux/noble R-4.5 | DBNMFrank_0.1.0.tar.gz |
2.9 KiB |
0.1.0 |
latest source/ R- | DBNMFrank_0.1.0.tar.gz |
2.9 KiB |
0.1.0 |
2026-04-26 source/ R- | DBNMFrank_0.1.0.tar.gz |
2.9 KiB |
0.1.0 |
2026-04-23 source/ R- | DBNMFrank_0.1.0.tar.gz |
2.9 KiB |
0.1.0 |
2025-04-20 source/ R- | DBNMFrank_0.1.0.tar.gz |
2.9 KiB |