bnmonitor
An Implementation of Sensitivity Analysis in Bayesian Networks
An implementation of sensitivity and robustness methods in Bayesian networks in R. It includes methods to perform parameter variations via a variety of co-variation schemes, to compute sensitivity functions and to quantify the dissimilarity of two Bayesian networks via distances and divergences. It further includes diagnostic methods to assess the goodness of fit of a Bayesian networks to data, including global, node and parent-child monitors. Reference: M. Leonelli, R. Ramanathan, R.L. Wilkerson (2022) doi:10.1016/j.knosys.2023.110882.
- Version0.2.2
- R version≥ 3.5.0
- LicenseGPL-3
- Needs compilation?No
- bnmonitor citation info
- Last release09/23/2024
Documentation
Team
Manuele Leonelli
Ramsiya Ramanathan
Show author detailsRolesAuthorRachel Wilkerson
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 452 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 14 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 4,711 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 26, 2024 with 75 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports12 packages
- Suggests3 packages