abn-package |
abn Package |
abn |
abn Package |
abn.Version |
abn Version Information |
abn.version |
abn Version Information |
adg |
Dataset related to average daily growth performance and abattoir findings in pigs commercial production. |
build.control |
Control the iterations in 'buildScoreCache' |
buildScoreCache |
Build a cache of goodness of fit metrics for each node in a DAG, possibly subject to user-defined restrictions |
compareDAG |
Compare two DAGs or EGs |
compareDag |
Compare two DAGs or EGs |
compareEG |
Compare two DAGs or EGs |
createAbnDag |
Create a legitimate DAGs |
createDag |
Create a legitimate DAGs |
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 |
ex0.dag.data |
Synthetic validation data set for use with abn library examples |
ex1.dag.data |
Synthetic validation data set for use with abn library examples |
ex2.dag.data |
Synthetic validation data set for use with abn library examples |
ex3.dag.data |
Validation data set for use with abn library examples |
ex4.dag.data |
Valdiation data set for use with abn library examples |
ex5.dag.data |
Valdiation data set for use with abn library examples |
ex6.dag.data |
Valdiation data set for use with abn library examples |
ex7.dag.data |
Valdiation data set for use with abn library examples |
expit |
Expit, Logit, and odds |
FCV |
Dataset related to Feline calicivirus infection among cats in Switzerland. |
fit.control |
Control the iterations in 'fitAbn' |
fitAbn |
Fit an additive Bayesian network model |
infoDag |
Compute standard information for a DAG. |
link.strength |
A function that returns the strengths of the edge connections in a Bayesian Network learned from observational data. |
linkStrength |
A function that returns the strengths of the edge connections in a Bayesian Network learned from observational data. |
linkstrength |
A function that returns the strengths of the edge connections in a Bayesian Network learned from observational data. |
logit |
Expit, Logit, and odds |
mb |
Compute the Markov blanket |
miData |
Empirical Estimation of the Entropy from a Table of Counts |
mostProbable |
Find most probable DAG structure |
odds |
Expit, Logit, and odds |
or |
Odds Ratio from a Table |
overview |
abn Package |
pigs.vienna |
Dataset related to diseases present in 'finishing pigs', animals about to enter the human food chain at an abattoir. |
plotAbn |
Plot an ABN graphic |
scoreContribution |
Compute the score's contribution in a network of each observation. |
search.heuristic |
A family of heuristic algorithms that aims at finding high scoring directed acyclic graphs |
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. |
simulate.abn |
Simulate from an ABN Network |
simulate.dag |
Simulate DAGs |
simulateAbn |
Simulate from an ABN Network |
simulateabn |
Simulate from an ABN Network |
simulateDag |
Simulate DAGs |
toGraphviz |
Convert a DAG into graphviz format |
tographviz |
Convert a DAG into graphviz format |
var33 |
simulated dataset from a DAG comprising of 33 variables |
version |
abn Version Information |