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spDBL

Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models

v1.0.2 · Jun 9, 2026 · MIT + file LICENSE

Description

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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Check History

OK 9 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 10, 2026

Dependency Network

Dependencies Reverse dependencies Rcpp matrixsampling invgamma deSolve ReacTran LaplacesDemon matrixcalc mniw ggpubr ggplot2 readr magrittr rlang scales spDBL

Version History

new 1.0.2 Jun 9, 2026