py39-spvcm (python/py-spvcm) Updated: 1 year, 3 months 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
10 build(s) found
| Builder | Build Number | Start Time | Elapsed Time | Watcher | Build Status |
|---|---|---|---|---|---|
| 10.11 | 232415 | 2023-08-18 2:57:59 | 0:07:24 | 75544 | build successful |
| 10.13 | 201878 | 2023-08-18 2:32:18 | 0:02:09 | 66390 | build successful |
| 10.15 | 152155 | 2023-08-18 2:23:36 | 0:01:54 | 46137 | build successful |
| 10.10 | 236022 | 2023-08-18 2:19:19 | 0:02:12 | 75432 | build successful |
| 13 | 44936 | 2023-08-18 2:13:05 | 0:01:41 | 10606 | build successful |
| 10.9 | 242508 | 2023-08-18 2:06:35 | 0:01:21 | 75121 | build successful |
| 10.8 | 144807 | 2023-08-18 2:00:32 | 0:01:54 | 45908 | build successful |
| 10.6.x86_64 | 167221 | 2023-08-18 1:57:18 | 0:00:22 | 48107 | failed install-dependencies |
| 10.7 | 156404 | 2023-08-18 1:57:12 | 0:02:21 | 47848 | build successful |
| 13.arm64 | 32055 | 2023-08-18 1:35:55 | 0:00:45 | 10463 | build successful |