spDBL
Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models
Provides tools for Bayesian learning of spatiotemporal dynamical mechanistic models. Includes methods for parameter estimation, simulation, and inference using hierarchical and state-space modeling approaches, following Banerjee, Chen, Frankenburg and Zhou (2025) <https://jmlr.org/papers/v26/22-0896.html>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.2 |
rolling linux/jammy R-4.5 | spDBL_1.0.2.tar.gz |
1.8 MiB |
1.0.2 |
rolling linux/noble R-4.5 | spDBL_1.0.2.tar.gz |
1.8 MiB |
1.0.2 |
rolling source/ R- | spDBL_1.0.2.tar.gz |
1.5 MiB |
1.0.2 |
latest linux/jammy R-4.5 | spDBL_1.0.2.tar.gz |
1.8 MiB |
1.0.2 |
latest linux/noble R-4.5 | spDBL_1.0.2.tar.gz |
1.8 MiB |
1.0.2 |
latest source/ R- | spDBL_1.0.2.tar.gz |
1.5 MiB |
1.0.2 |
2026-04-23 source/ R- | spDBL_1.0.2.tar.gz |
0 B |