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BayesForge  

Bayesian Inference using 'numpyro' and 'XLA'
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BayesForge", "0.0.1")



Attach the package and use:
library("BayesForge")
Maintained by
Sebastian Sosa
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-08
Latest Update: 2026-06-08
Description:
A high-performance probabilistic programming library that aims to unify the modeling experience by providing an intuitive model-building syntax together with the flexibility of low-level abstraction coding. It also includes pre-built functions for high-level abstraction and supports hardware-accelerated computation for improved scalability, including parallelization, vectorization, and execution on CPU (Central Processing Unit), GPU (Graphics Processing Unit), or TPU (Tensor Processing Unit) using 'JAX' (Just-In-Time compiled Accelerated linear algebra) as the computational backend: Sosa (2026) <doi:10.64898/2026.01.19.700318>.
How to cite:
Sebastian Sosa (2026). BayesForge: Bayesian Inference using 'numpyro' and 'XLA'. R package version 0.0.1, https://cran.r-project.org/web/packages/BayesForge. Accessed 12 Sep. 2026.
Previous versions and publish date:
No previous versions
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Complete documentation for BayesForge
Functions, R codes and Examples using the BayesForge R package
Full BayesForge package functions and examples
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