BayesianNetwork
Authors: Paul Govan
Abstract: BayesianNetwork is a Shiny web application designed for Bayesian Network modeling and analysis, leveraging the capabilities of the bnlearn package for Bayesian Network learning. The app offers robust features, including structural learning algorithms for discovering network structures, with support for both discrete and continuous variables. Additionally, it includes parameter learning methods for estimating network parameters, tools for incorporating evidence and performing Bayesian inference, and utilities for evaluating the significance of nodes and connections within the network. BayesianNetwork aims to be a versatile tool, accessible to researchers, educators, and students alike, enabling both advanced analysis and ease of use.
Full Description: For further information, including detailed documentation, examples, and background on the project, visit the official project site at Bayesian Network Modeling and Analysis • BayesianNetwork or explore the accompanying article in JOSS at Journal of Open Source Software: BayesianNetwork: Interactive Bayesian Network Modeling and Analysis.
Shiny app: BayesianNetwork
Repo: GitHub - paulgovan/BayesianNetwork: Bayesian Network Modeling and Analysis
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