| abn-package | abn Package |
| abn | abn Package |
| adg | Dataset related to average daily growth performance and abattoir findings in pigs commercial production. |
| 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 |
| 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. |
| 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 |