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spDBL  

Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models
View on CRAN: Click here


Download and install spDBL package within the R console
Install from CRAN:
install.packages("spDBL")

Install from Github:
library("remotes")
install_github("cran/spDBL")

Install by package version:
library("remotes")
install_version("spDBL", "1.0.2")



Attach the package and use:
library("spDBL")
Maintained by
Xiang Chen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-09
Latest Update: 2026-06-09
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>.
How to cite:
Xiang Chen (2026). spDBL: Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models. R package version 1.0.2, https://cran.r-project.org/web/packages/spDBL. Accessed 25 Jun. 2026.
Previous versions and publish date:
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View spDBL citation profile
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Complete documentation for spDBL
Functions, R codes and Examples using the spDBL R package
Full spDBL package functions and examples
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