Modelling Multivariate Data with Additive Bayesian Networks

---

Documentation for package ‘abn’ version 3.1.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

AIC.abnFit	Print AIC of objects of class 'abnFit'
BIC.abnFit	Print BIC of objects of class 'abnFit'
build.control	Control the iterations in 'buildScoreCache'
check.valid.fitControls	Simple check on the control parameters
coef.abnFit	Print coefficients of objects of class 'abnFit'
compareDag	Compare two DAGs or EGs
compareEG	Compare two DAGs or EGs
discretization	Discretization of a Possibly Continuous Data Frame of Random Variables based on their distribution
entropyData	Computes an Empirical Estimation of the Entropy from a Table of Counts
essentialGraph	Construct the essential graph
expit	expit of proportions
expit_cpp	expit function
family.abnFit	Print family of objects of class 'abnFit'
fit.control	Control the iterations in 'fitAbn'
getMSEfromModes	Extract Standard Deviations from all Gaussian Nodes
infoDag	Compute standard information for a DAG.
linkStrength	Returns the strengths of the edge connections in a Bayesian Network learned from observational data
logit	Logit of proportions
logit_cpp	logit functions
logLik.abnFit	Print logLik of objects of class 'abnFit'
mb	Compute the Markov blanket
miData	Empirical Estimation of the Entropy from a Table of Counts
modes2coefs	Convert modes to fitAbn.mle$coefs structure
mostProbable	Find most probable DAG structure
nobs.abnFit	Print number of observations of objects of class 'abnFit'
odds	Probability to odds
or	Odds Ratio from a matrix
plot.abnDag	Plots DAG from an object of class 'abnDag'
plot.abnFit	Plot objects of class 'abnFit'
plot.abnHeuristic	Plot objects of class 'abnHeuristic'
plot.abnHillClimber	Plot objects of class 'abnHillClimber'
plot.abnMostprobable	Plot objects of class 'abnMostprobable'
print.abnCache	Print objects of class 'abnCache'
print.abnDag	Print objects of class 'abnDag'
print.abnFit	Print objects of class 'abnFit'
print.abnHeuristic	Print objects of class 'abnHeuristic'
print.abnHillClimber	Print objects of class 'abnHillClimber'
print.abnMostprobable	Print objects of class 'abnMostprobable'
scoreContribution	Compute the score's contribution in a network of each observation.
searchHeuristic	A family of heuristic algorithms that aims at finding high scoring directed acyclic graphs
searchHillClimber	Find high scoring directed acyclic graphs using heuristic search.
simulateAbn	Simulate data from a fitted additive Bayesian network.
simulateDag	Simulate a DAG with with arbitrary arcs density
skewness	Computes skewness of a distribution
summary.abnDag	Prints summary statistics from an object of class 'abnDag'
summary.abnFit	Print summary of objects of class 'abnFit'
summary.abnMostprobable	Print summary of objects of class 'abnMostprobable'
toGraphviz	Convert a DAG into graphviz format