py313-spvcm (python/py-spvcm) Updated: 1 month, 3 weeks ago Add to my watchlist
Multilevel spatially-correlated variance components models (spvcm)The PySAL spvcm is a package to estimate spatially-correlated variance components models/varying intercept models. In addition to a general toolkit to conduct Gibbs sampling in Python, the package also provides an interface to PyMC3 and CODA. For a complete overview, consult the walkthrough.
Version: 0.3.0 License: BSD
GitHub
15 build(s) found
| Builder | Build Number | Start Time | Elapsed Time | Watcher | Build Status |
|---|---|---|---|---|---|
| 10.11 | 287087 | 2025-02-14 16:43:26 | 0:06:42 | 95498 | build successful |
| 10.14 | 229269 | 2025-02-14 16:27:23 | 0:01:16 | 76948 | build successful |
| 10.8 | 201463 | 2025-02-14 15:48:00 | 0:00:37 | 65799 | failed install-dependencies |
| 10.13 | 255422 | 2025-02-14 15:45:15 | 0:00:51 | 86315 | build successful |
| 10.12 | 297129 | 2025-02-14 15:42:01 | 0:01:03 | 94249 | build successful |
| 10.7 | 215798 | 2025-02-14 15:38:55 | 0:00:40 | 67761 | failed install-dependencies |
| 10.10 | 293912 | 2025-02-14 15:34:07 | 0:01:02 | 95336 | build successful |
| 10.9 | 301364 | 2025-02-14 15:30:20 | 0:00:41 | 95006 | failed install-dependencies |
| 11 | 177799 | 2025-02-14 15:19:53 | 0:00:55 | 55963 | build successful |
| 10.15 | 206204 | 2025-02-14 15:13:32 | 0:00:49 | 66012 | build successful |
| 12 | 128667 | 2025-02-14 15:12:49 | 0:00:46 | 44843 | build successful |
| 10.6.x86_64 | 229371 | 2025-02-14 15:08:51 | 0:00:55 | 68101 | failed install-dependencies |
| 10.6 | 193720 | 2025-02-14 14:53:44 | 0:00:30 | 68050 | failed install-dependencies |
| 14 | 56923 | 2025-02-14 14:49:13 | 0:00:21 | 18783 | build successful |
| 14.arm64 | 52140 | 2025-02-14 14:47:58 | 0:00:46 | 18425 | build successful |