wiseR: A Shiny Application for End-to-End Bayesian Decision Network Analysis and Web-Deployment

A Shiny application for learning Bayesian Decision Networks from data. This package can be used for probabilistic reasoning (in the observational setting), causal inference (in the presence of interventions) and learning policy decisions (in Decision Network setting). Functionalities include end-to-end implementations for data-preprocessing, structure-learning, exact inference, approximate inference, extending the learned structure to Decision Networks and policy optimization using statistically rigorous methods such as bootstraps, resampling, ensemble-averaging and cross-validation. In addition to Bayesian Decision Networks, it also features correlation networks, community-detection, graph visualizations, graph exports and web-deployment of the learned models as Shiny dashboards.

Version: 1.0.1
Depends: R (≥ 3.5.0)
Imports: Rgraphviz, RBGL, graph, bnlearn, HydeNet, rhandsontable, shiny, shinydashboard, dplyr, visNetwork, shinyWidgets, missRanger, tools, shinyalert, shinycssloaders, rintrojs, arules, psych, DescTools, DT, linkcomm, igraph, parallel, shinyBS
Suggests: knitr, rmarkdown, rcompanion
Published: 2018-11-29
Author: Tavpritesh Sethi [aut, cre], Shubham Maheshwari [aut]
Maintainer: Tavpritesh Sethi <tavpriteshsethi at iiitd.ac.in>
Contact: Tavpritesh Sethi<tavpriteshsethi@iiitd.ac.in>,Shubham Maheshwari<shubham14101@iiitd.ac.in>
BugReports: https://github.com/SAFE-ICU/wiseR/issues
License: GPL-3 | file LICENSE
URL: https://github.com/SAFE-ICU/wiseR
NeedsCompilation: no
Materials: README
CRAN checks: wiseR results

Documentation:

Reference manual: wiseR.pdf

Downloads:

Package source: wiseR_1.0.1.tar.gz
Windows binaries: r-devel: wiseR_1.0.1.zip, r-release: wiseR_1.0.1.zip, r-oldrel: wiseR_1.0.1.zip
macOS binaries: r-release (arm64): wiseR_1.0.1.tgz, r-oldrel (arm64): wiseR_1.0.1.tgz, r-release (x86_64): wiseR_1.0.1.tgz, r-oldrel (x86_64): wiseR_1.0.1.tgz

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