GRelevance
Graph-Based k-Sample Comparisons and Relevance Analysis in High Dimensions
We propose two distribution-free test statistics based on between-sample edge counts and measure the degree of relevance by standardized counts. Users can set edge costs in the graph to compare the parameters of the distributions. Methods for comparing distributions are as described in: Xiaoping Shi (2021) <arXiv:2107.00728>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling source/ R- | GRelevance_1.0.tar.gz |
4.8 KiB |
1.0 |
rolling linux/jammy R-4.5 | GRelevance_1.0.tar.gz |
32.6 KiB |
1.0 |
rolling linux/noble R-4.5 | GRelevance_1.0.tar.gz |
32.5 KiB |
1.0 |
latest source/ R- | GRelevance_1.0.tar.gz |
4.8 KiB |
1.0 |
latest linux/jammy R-4.5 | GRelevance_1.0.tar.gz |
32.6 KiB |
1.0 |
latest linux/noble R-4.5 | GRelevance_1.0.tar.gz |
32.5 KiB |
1.0 |
2026-04-23 source/ R- | GRelevance_1.0.tar.gz |
4.8 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | GRelevance_1.0.zip |
35.7 KiB |
1.0 |
2025-04-20 source/ R- | GRelevance_1.0.tar.gz |
4.8 KiB |