bnmonitor is a package for sensitivity analysis and robustness in Bayesian networks (BNs). If you use the package in your work please consider citing as

#> To cite package 'bnmonitor' in publications use:
#>   Leonelli M, Ramanathan R, Wilkerson RL (2023). "Sensitivity and
#>   robustness analysis in Bayesian networks with the bnmonitor R
#>   package." _Knowledge-Based Systems_, *278*, 110882.
#>   doi:10.1016/j.knosys.2023.110882
#>   <>.
#> A BibTeX entry for LaTeX users is
#>   @Article{,
#>     title = {Sensitivity and robustness analysis in {Bayesian} networks with the bnmonitor R package},
#>     author = {Manuele Leonelli and Ramsiya Ramanathan and Rachel L. Wilkerson},
#>     journal = {Knowledge-Based Systems},
#>     year = {2023},
#>     volume = {278},
#>     pages = {110882},
#>     doi = {10.1016/j.knosys.2023.110882},
#>   }


The package bnmonitor can be installed from CRAN using the command


and loaded in R with


Note that bnmonitor requires the package gRain which, while on CRAN, depends on packages that are on Bioconductor both directly and through the gRbase package, which depends on RBGL:

BiocManager::install(c("graph", "Rgraphviz", "RBGL"))


bnmonitor provides a suite of function to investigate either a data-learnt or an expert elicited BN. Its functions can be classified into the following main areas:

Refer to the articles section for case studies showcasing the use of the bnmonitor functions.

Papers where bnmonitor is used