# Bayesian network structure learning, parameter learning and inference

## Documentation for package ‘bnlearn’ version 3.3

- DESCRIPTION file.

## Help Pages

A B C D E F G H I L M N O P R S T U V W misc

bnlearn-package | Bayesian network structure learning, parameter learning and inference.

## -- A --

acyclic | Utilities to manipulate graphs
AIC.bn | Score of the Bayesian network
AIC.bn.fit | Utilities to manipulate fitted Bayesian networks
alarm | ALARM Monitoring System (synthetic) data set
all.equal.bn | Compare two different Bayesian networks
amat | Miscellaneous utilities
amat<- | Miscellaneous utilities
aracne | Local discovery structure learning algorithms
arc operations | Drop, add or set the direction of an arc
arc.strength | Measure arc strength
arcs | Miscellaneous utilities
arcs<- | Miscellaneous utilities
as.bn | Build a model string from a Bayesian network and vice versa
as.bn.character | Build a model string from a Bayesian network and vice versa
as.bn.fit | Import and export networks from the gRain package
as.bn.fit.grain | Import and export networks from the gRain package
as.bn.graphAM | Import and export networks from the graph package
as.bn.graphNEL | Import and export networks from the graph package
as.character.bn | Build a model string from a Bayesian network and vice versa
as.grain | Import and export networks from the gRain package
as.grain.bn.fit | Import and export networks from the gRain package
as.graphAM | Import and export networks from the graph package
as.graphAM.bn | Import and export networks from the graph package
as.graphAM.bn.fit | Import and export networks from the graph package
as.graphNEL | Import and export networks from the graph package
as.graphNEL.bn | Import and export networks from the graph package
as.graphNEL.bn.fit | Import and export networks from the graph package
asia | Asia (synthetic) data set by Lauritzen and Spiegelhalter
averaged.network | Measure arc strength

## -- B --

BIC.bn | Score of the Bayesian network
BIC.bn.fit | Utilities to manipulate fitted Bayesian networks
blacklist | Miscellaneous utilities
bn class | The bn class structure
bn-class | The bn class structure
bn.boot | Parametric and nonparametric bootstrap of Bayesian networks
bn.cv | Cross-validation for Bayesian networks
bn.fit | Fit the parameters of a Bayesian network
bn.fit class | The bn.fit class structure
bn.fit plots | Plot fitted Bayesian networks
bn.fit utilities | Utilities to manipulate fitted Bayesian networks
bn.fit-class | The bn.fit class structure
bn.fit.barchart | Plot fitted Bayesian networks
bn.fit.dnode | The bn.fit class structure
bn.fit.dotplot | Plot fitted Bayesian networks
bn.fit.gnode | The bn.fit class structure
bn.fit.histogram | Plot fitted Bayesian networks
bn.fit.qqplot | Plot fitted Bayesian networks
bn.fit.xyplot | Plot fitted Bayesian networks
bn.kcv class | The bn.kcv class structure
bn.kcv-class | The bn.kcv class structure
bn.moments | Structure variability of Bayesian networks
bn.net | Fit the parameters of a Bayesian network
bn.strength | The bn.strength class structure
bn.strength class | The bn.strength class structure
bn.strength-class | The bn.strength class structure
bn.var | Structure variability of Bayesian networks
bnlearn | Bayesian network structure learning, parameter learning and inference.
boot.strength | Measure arc strength

## -- C --

cextend | Equivalence classes, moral graphs and consistent extenions
children | Miscellaneous utilities
children<- | Miscellaneous utilities
choose.direction | Try to infer the direction of an undirected arc
chow.liu | Local discovery structure learning algorithms
ci.test | Independence and Conditional Independence Tests
ci.test.character | Independence and Conditional Independence Tests
ci.test.data.frame | Independence and Conditional Independence Tests
ci.test.default | Independence and Conditional Independence Tests
ci.test.factor | Independence and Conditional Independence Tests
ci.test.numeric | Independence and Conditional Independence Tests
coef.bn.fit | Utilities to manipulate fitted Bayesian networks
coef.bn.fit.dnode | Utilities to manipulate fitted Bayesian networks
coef.bn.fit.gnode | Utilities to manipulate fitted Bayesian networks
compare | Compare two different Bayesian networks
constraint-based algorithms | Constraint-based structure learning algorithms
coronary | Coronary Heart Disease data set
cpdag | Equivalence classes, moral graphs and consistent extenions
cpdist | Perform conditional probability queries
cpquery | Perform conditional probability queries
custom.fit | Fit the parameters of a Bayesian network
custom.strength | Measure arc strength

## -- D --

deal integration | bnlearn - deal package integration
degree | Miscellaneous utilities
degree-method | Miscellaneous utilities
directed | Utilities to manipulate graphs
directed.arcs | Miscellaneous utilities
discretize | Discretize data to learn discrete Bayesian networks
drop.arc | Drop, add or set the direction of an arc
dsep | Test d-separation

## -- E --

empty.graph | Generate empty or random graphs

## -- F --

fast.iamb | Constraint-based structure learning algorithms
fitted.bn.fit | Utilities to manipulate fitted Bayesian networks
fitted.bn.fit.dnode | Utilities to manipulate fitted Bayesian networks
fitted.bn.fit.gnode | Utilities to manipulate fitted Bayesian networks

## -- G --

gaussian.test | Synthetic (continuous) data set to test learning algorithms
gRain integration | Import and export networks from the gRain package
graph generation utilities | Generate empty or random graphs
graph integration | Import and export networks from the graph package
graph utilities | Utilities to manipulate graphs
graphviz.plot | Advanced Bayesian network plots
gs | Constraint-based structure learning algorithms

## -- H --

hailfinder | The HailFinder weather forecast system (synthetic) data set
hamming | Compare two different Bayesian networks
hc | Score-based structure learning algorithms
hybrid algorithms | Hybrid structure learning algorithms

## -- I --

iamb | Constraint-based structure learning algorithms
in.degree | Miscellaneous utilities
incident.arcs | Miscellaneous utilities
incoming.arcs | Miscellaneous utilities
insurance | Insurance evaluation network (synthetic) data set
inter.iamb | Constraint-based structure learning algorithms

## -- L --

leaf.nodes | Miscellaneous utilities
learn.mb | Discover the structure around a single node
learn.nbr | Discover the structure around a single node
learning.test | Synthetic (discrete) data set to test learning algorithms
lizards | Lizards' perching behaviour data set
local discovery algorithms | Local discovery structure learning algorithms
logLik.bn | Score of the Bayesian network
logLik.bn.fit | Utilities to manipulate fitted Bayesian networks

## -- M --

marks | Examination marks data set
mb | Miscellaneous utilities
misc utilities | Miscellaneous utilities
mmhc | Hybrid structure learning algorithms
mmpc | Local discovery structure learning algorithms
model string utilities | Build a model string from a Bayesian network and vice versa
model2network | Build a model string from a Bayesian network and vice versa
modelstring | Build a model string from a Bayesian network and vice versa
modelstring<- | Build a model string from a Bayesian network and vice versa
moral | Equivalence classes, moral graphs and consistent extenions

## -- N --

naive.bayes | Naive Bayes classifiers
narcs | Miscellaneous utilities
nbr | Miscellaneous utilities
node ordering utilities | Utilities dealing with partial node orderings
node.ordering | Utilities dealing with partial node orderings
nodes | Miscellaneous utilities
nodes-method | Miscellaneous utilities
nparams | Miscellaneous utilities
ntests | Miscellaneous utilities

## -- O --

ordering2blacklist | Utilities dealing with partial node orderings
out.degree | Miscellaneous utilities
outgoing.arcs | Miscellaneous utilities

## -- P --

parallel integration | bnlearn - snow/parallel package integration
parents | Miscellaneous utilities
parents<- | Miscellaneous utilities
path | Utilities to manipulate graphs
pdag2dag | Utilities to manipulate graphs
plot.bn | Plot a Bayesian network
predict.bn.fit | Utilities to manipulate fitted Bayesian networks
predict.bn.fit.dnode | Utilities to manipulate fitted Bayesian networks
predict.bn.fit.gnode | Utilities to manipulate fitted Bayesian networks
predict.bn.naive | Naive Bayes classifiers
predict.bn.tan | Naive Bayes classifiers

## -- R --

random.graph | Generate empty or random graphs
rbn | Generate random data from a given Bayesian network
rbn.bn | Generate random data from a given Bayesian network
rbn.bn.fit | Generate random data from a given Bayesian network
read.bif | Read and write BIF, NET and DSC files
read.dsc | Read and write BIF, NET and DSC files
read.net | Read and write BIF, NET and DSC files
relevant | Identify Relevant Nodes Without Learning the Bayesian network
residuals.bn.fit | Utilities to manipulate fitted Bayesian networks
residuals.bn.fit.dnode | Utilities to manipulate fitted Bayesian networks
residuals.bn.fit.gnode | Utilities to manipulate fitted Bayesian networks
reverse.arc | Drop, add or set the direction of an arc
root.nodes | Miscellaneous utilities
rsmax2 | Hybrid structure learning algorithms

## -- S --

score | Score of the Bayesian network
score-based algorithms | Score-based structure learning algorithms
set.arc | Drop, add or set the direction of an arc
shd | Compare two different Bayesian networks
si.hiton.pc | Local discovery structure learning algorithms
single-node local discovery | Discover the structure around a single node
skeleton | Utilities to manipulate graphs
snow integration | bnlearn - snow/parallel package integration
strength.plot | Arc strength plot
subgraph | Utilities to manipulate graphs

## -- T --

tabu | Score-based structure learning algorithms
tiers2blacklist | Utilities dealing with partial node orderings
tree.bayes | Naive Bayes classifiers

## -- U --

undirected.arcs | Miscellaneous utilities

## -- V --

vstructs | Equivalence classes, moral graphs and consistent extenions

## -- W --

whitelist | Miscellaneous utilities
write.bif | Read and write BIF, NET and DSC files
write.dsc | Read and write BIF, NET and DSC files
write.net | Read and write BIF, NET and DSC files

## -- misc --

$<-.bn.fit | Fit the parameters of a Bayesian network