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bnns  

Bayesian Neural Network with 'Stan'
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("bnns", "0.1.2")



Attach the package and use:
library("bnns")
Maintained by
Swarnendu Chatterjee
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-01-13
Latest Update: 2025-01-13
Description:
Offers a flexible formula-based interface for building and training Bayesian Neural Networks powered by 'Stan'. The package supports modeling complex relationships while providing rigorous uncertainty quantification via posterior distributions. With features like user chosen priors, clear predictions, and support for regression, binary, and multi-class classification, it is well-suited for applications in clinical trials, finance, and other fields requiring robust Bayesian inference and decision-making. References: Neal(1996) <doi:10.1007/978-1-4612-0745-0>.
How to cite:
Swarnendu Chatterjee (2025). bnns: Bayesian Neural Network with 'Stan'. R package version 0.1.2, https://cran.r-project.org/web/packages/bnns. Accessed 26 Jun. 2026.
Previous versions and publish date:
0.1.2 (2025-01-13 18:30)
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Complete documentation for bnns
Functions, R codes and Examples using the bnns R package
Full bnns package functions and examples
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