mdw
Maximum Diversity Weighting
Dimension-reduction methods aim at defining a score that maximizes signal diversity. Three approaches, tree weight, maximum entropy weights, and maximum variance weights are provided. These methods are described in He and Fong (2019) <DOI:10.1002/sim.8212>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2024.8-1 |
rolling linux/jammy R-4.5 | mdw_2024.8-1.tar.gz |
83.4 KiB |
2024.8-1 |
rolling linux/noble R-4.5 | mdw_2024.8-1.tar.gz |
83.4 KiB |
2024.8-1 |
rolling source/ R- | mdw_2024.8-1.tar.gz |
47.4 KiB |
2024.8-1 |
latest linux/jammy R-4.5 | mdw_2024.8-1.tar.gz |
83.4 KiB |
2024.8-1 |
latest linux/noble R-4.5 | mdw_2024.8-1.tar.gz |
83.4 KiB |
2024.8-1 |
latest source/ R- | mdw_2024.8-1.tar.gz |
47.4 KiB |
2024.8-1 |
2026-04-26 source/ R- | mdw_2024.8-1.tar.gz |
47.4 KiB |
2024.8-1 |
2026-04-23 source/ R- | mdw_2024.8-1.tar.gz |
47.4 KiB |
2024.8-1 |
2026-04-09 windows/windows R-4.5 | mdw_2024.8-1.zip |
86.6 KiB |
2024.8-1 |
2025-04-20 source/ R- | mdw_2024.8-1.tar.gz |
47.4 KiB |