hgwrr
Hierarchical and Geographically Weighted Regression
This model divides coefficients into three types, i.e., local fixed effects, global fixed effects, and random effects (Hu et al., 2022)<doi:10.1177/23998083211063885>. If data have spatial hierarchical structures (especially are overlapping on some locations), it is worth trying this model to reach better fitness.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.6-2 |
rolling source/ R- | hgwrr_0.6-2.tar.gz |
951.4 KiB |
0.6-2 |
rolling linux/jammy R-4.5 | hgwrr_0.6-2.tar.gz |
951.4 KiB |
0.6-2 |
rolling linux/noble R-4.5 | hgwrr_0.6-2.tar.gz |
951.4 KiB |
0.6-2 |
latest source/ R- | hgwrr_0.6-2.tar.gz |
951.4 KiB |
0.6-2 |
latest linux/jammy R-4.5 | hgwrr_0.6-2.tar.gz |
951.4 KiB |
0.6-2 |
latest linux/noble R-4.5 | hgwrr_0.6-2.tar.gz |
951.4 KiB |
0.6-2 |
2026-04-23 source/ R- | hgwrr_0.6-2.tar.gz |
951.4 KiB |
0.6-2 |
2026-04-09 windows/windows R-4.5 | hgwrr_0.6-2.zip |
1.6 MiB |
0.6-1 |
2025-04-20 source/ R- | hgwrr_0.6-1.tar.gz |
951.4 KiB |