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>.
Version: 0.2.2 Depends: R (≥ 3.5.0) Imports: bnlearn, dplyr, ggplot2, gRain, gRbase, graphics, igraph, methods, purrr, qgraph, RColorBrewer, reshape2, rlang, tidyr Suggests: testthat, knitr, rmarkdown Published: 2024-09-23 DOI: 10.32614/CRAN.package.bnmonitor Author: Manuele Leonelli [aut, cre], Ramsiya Ramanathan [aut], Rachel Wilkerson [aut] Maintainer: Manuele Leonelli <manuele.leonelli at ie.edu> License: GPL-3 URL: https://manueleleonelli.github.io/bnmonitor/, https://github.com/manueleleonelli/bnmonitor NeedsCompilation: no Citation: bnmonitor citation info Materials: README CRAN checks: bnmonitor results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=bnmonitor to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4