| buildscorecache | Build a cache of goodness of fit metrics for each node in a DAG, possibly subject to user defined restrictions |
| buildscorecache.mle | Build a cache of goodness of fit metrics based on Information Theoretic for each node in a DAG, possibly subject to user defined restrictions |
| compareDag | Compare two 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 | Plot an ABN graphic |
| 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 |
| expit_cpp | logit and logit functions |
| fitabn | Fit an additive Bayesian network model |
| fitabn.mle | Fit an additive Bayesian network model based on maximum likelihood estimation. |
| infoDag | Compute standard information for a DAG. |
| link.strength | A function that returns the strengths of the edge connections in a Bayesian Network learned form observational data. |
| logit | Expit, Logit and odds |
| logit_cpp | logit and logit functions |
| mb | Compute the Markov blanket |
| miData | Computes an Empirical Estimation of the Entropy from a Table of Counts |
| mostprobable | Find most probable DAG structure |
| odds | Expit, Logit and odds |
| or | Odd ratio from a table |
| 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 |
| search.heuristic | A familly of heuristic algorithms that aims at finding high scoring directed acyclic graphs |
| search.hillclimber | Find high scoring directed acyclic graphs using heuristic search. |
| simulateabn | Simulate from an ABN network |
| simulateDag | Simulate DAGs |
| tographviz | Convert a dag into graphviz format |
| var33 | simulated dataset from a DAG comprising of 33 variables |