graph integration

as.bn.graphNEL

as.bn.graphAM

as.graphNEL

as.graphAM

as.graphNEL.bn

as.graphNEL.bn.fit

as.graphAM.bn

as.graphAM.bn.fit

an object of class <code>bn</code>, <code>bn.fit</code>, <code>graphNEL</code>,
 <code>graphAM</code>.

Convert <code>bn</code> and <code>bn.fit</code> objects to <code>graphNEL</code> and
 <code>graphAM</code> objects and vice versa.

multivariate

utilities

Bayesian network structure learning, parameter learning and
inference.
This package implements constraint-based (GS, IAMB, Inter-IAMB, Fast-IAMB,
MMPC, Hiton-PC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing
and Tabu Search) and hybrid (MMHC and RSMAX2) structure learning algorithms
for discrete, Gaussian and conditional Gaussian networks, along with many
score functions and conditional independence tests.
The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are
also implemented.
Some utility functions (model comparison and manipulation, random data
generation, arc orientation testing, simple and advanced plots) are
included, as well as support for parameter estimation (maximum likelihood
and Bayesian) and inference, conditional probability queries and
cross-validation. Development snapshots with the latest bugfixes are
available from <http://www.bnlearn.com>.

Marco Scutari

bnlearn

Bayesian Network Structure Learning, Parameter Learning and
Inference

graph integration function

Import and export networks from the graph package — graph integration

Import and export networks from the graph package

graph integration: Import and export networks from the graph package

Description

Usage

Arguments

Value

Examples