pcalg integration

as.bn.pcAlgo

an object of class <code>pcAlgo</code>.

extra arguments from the generic method (currently ignored).

&#8230;

a boolean value. If <code>FALSE</code> the returned network will
 not be checked for cycles.

check.cycles

Convert <code>pcAlgo</code> objects to <code>bn</code> objects.

utilities

interfaces to other packages

Bayesian network structure learning, parameter learning and
inference.
This package implements constraint-based (PC, 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>.

pcalg integration: Import and export networks from the pcalg package

Description

Usage

Arguments

Value