Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models
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Overview
About
Maintained by Xiang ChenCRAN page ↗
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.
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Slowest check: 4.7 min · r-devel-windows-x86_64
Status changes
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK9 OK2026-06-10
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Documentation
In release 1.0.2
READMEYes · 726 wordsVignettesYes · 1 · dynamicNEWSNoCitation fileYes · cites a publicationWebsitenot declared in DESCRIPTION
- Help pages
- 73 (1 internal)includes a package overview page
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 1%
- Documented parameters
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- Return-value docs
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People (2)
Author, Maintainer since 1.0.2 (2026)
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Releases (1)
- 1.0.2Latest2026-06-09 · current release
- RR 4.6.0 released · 2026-04-24
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Package metadata
- First published
- 2026-06-09
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.0
- Bundled data
- 735 KB / 1 file
- Download size
- 1.6 MB
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