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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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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

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new 1.0.2 Jun 9, 2026