emission1000

Simulated data from the Emission example (also known as the Waste Incinerator example)

Belief propagation methods in Bayesian Networks to propagate evidence through the network. The implementation of these methods are based on the article: Cowell, RG (2005). Local Propagation in Conditional Gaussian Bayesian Networks <https://www.jmlr.org/papers/v6/cowell05a.html>. For details please see Yu et. al. (2020) BayesNetBP: An R Package for Probabilistic Reasoning in Bayesian Networks <doi:10.18637/jss.v094.i03>. The optional 'cyjShiny' package for running the Shiny app is available at <https://github.com/cytoscape/cyjShiny>. Please see the example in the documentation of 'runBayesNetApp' function for installing 'cyjShiny' package from GitHub.

Han Yu

BayesNetBP

Bayesian Network Belief Propagation

emission1000 function

The data set <code>emission1000</code> contains two objects:<dl class="dl-horizontal">
 <dt><code>data</code></dt><dd>a <code>data.frame</code> object of 1000 observations and 3 discrete variables and 6 continuous variables.</dd>
 <dt><code>dag</code></dt><dd>a <code>graphNEL</code> object specifying the network structure.</dd>
</dl>

Format

A simulated data from the Emission example — emission1000

The data set <code>emission1000</code> contains two objects:<dl class='dl-horizontal'>
 <dt><code>data</code></dt><dd>a <code>data.frame</code> object of 1000 observations and 3 discrete variables and 6 continuous variables.</dd>
 <dt><code>dag</code></dt><dd>a <code>graphNEL</code> object specifying the network structure.</dd>
</dl>

emission1000: A simulated data from the Emission example

Description

Usage

Arguments

Format

References