bnlearn: Bayesian Network Structure Learning, Parameter Learning and Inference
Version 4.1.1

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 .

AuthorMarco Scutari
Date of publication2017-03-26 07:40:17 UTC
MaintainerMarco Scutari <marco.scutari@gmail.com>
LicenseGPL (>= 2)
Version4.1.1
URL http://www.bnlearn.com/
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("bnlearn")

Getting started

Package overview

Popular man pages

alarm: ALARM Monitoring System (synthetic) data set
arcops: Drop, add or set the direction of an arc or an edge
bnlearn-package: Bayesian network structure learning, parameter learning and...
compare: Compare two different Bayesian networks
foreign: Read and write BIF, NET, DSC and DOT files
preprocessing: Pre-process data to better learn Bayesian networks
score: Score of the Bayesian network
See all...

All man pages Function index File listing

Man pages

alarm: ALARM Monitoring System (synthetic) data set
alpha.star: Estimate the Optimal Imaginary Sample Size for BDe(u)
arcops: Drop, add or set the direction of an arc or an edge
arc.strength: Measure arc strength
asia: Asia (synthetic) data set by Lauritzen and Spiegelhalter
bnboot: Parametric and nonparametric bootstrap of Bayesian networks
bn.class: The bn class structure
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.methods: Utilities to manipulate fitted Bayesian networks
bn.fit.plots: Plot fitted Bayesian networks
bn.kcv.class: The bn.kcv class structure
bnlearn-package: Bayesian network structure learning, parameter learning and...
bn.strength-class: The bn.strength class structure
choose.direction: Try to infer the direction of an undirected arc
ci.test: Independence and Conditional Independence Tests
clgaussian-test: Synthetic (mixed) data set to test learning algorithms
compare: Compare two different Bayesian networks
configs: Construct configurations of discrete variables
constraint: Constraint-based structure learning algorithms
coronary: Coronary Heart Disease data set
cpdag: Equivalence classes, moral graphs and consistent extensions
cpquery: Perform conditional probability queries
deal: bnlearn - deal package integration
dsep: Test d-separation
foreign: Read and write BIF, NET, DSC and DOT files
gaussian-test: Synthetic (continuous) data set to test learning algorithms
gRain: Import and export networks from the gRain package
graph: Utilities to manipulate graphs
graphgen: Generate empty or random graphs
graphpkg: Import and export networks from the graph package
graphviz.plot: Advanced Bayesian network plots
hailfinder: The HailFinder weather forecast system (synthetic) data set
hc: Score-based structure learning algorithms
hybrid: Hybrid structure learning algorithms
impute: Predict or Impute Missing Data from a Bayesian Network
insurance: Insurance evaluation network (synthetic) data set
learn: Discover the structure around a single node
learning-test: Synthetic (discrete) data set to test learning algorithms
lizards: Lizards' perching behaviour data set
marks: Examination marks data set
mb: Miscellaneous utilities
mmpc: Local discovery structure learning algorithms
modelstring: Build a model string from a Bayesian network and vice versa
naive.bayes: Naive Bayes classifiers
ordering: Utilities dealing with partial node orderings
parallel: bnlearn - snow/parallel package integration
plot.bn: Plot a Bayesian network
plot.bn.strength: Plot arc strengths derived from bootstrap
preprocessing: Pre-process data to better learn Bayesian networks
rbn: Simulate random data from a given Bayesian network
relevant: Identify Relevant Nodes Without Learning the Bayesian network
score: Score of the Bayesian network
strength.plot: Arc strength plot
test.counter: Manipulating the test counter

Functions

$<-.bn.fit Man page
AIC.bn Man page Source code
AIC.bn.fit Man page Source code
BIC.bn Man page Source code
BIC.bn.fit Man page Source code
acyclic Man page Source code
alarm Man page
all.equal.bn Man page Source code
all.equal.bn.fit Source code
allsubs.test Source code
alpha.star Man page Source code
alpha.star.backend Source code
amat Man page Source code
amat2arcs Source code
amat<- Man page
ancestors Man page Source code
aracne Man page Source code
aracne.backend Source code
arc operations Man page
arc.operations Source code
arc.strength Man page Source code
arc.strength.boot Source code
arc.strength.custom Source code
arc.strength.score Source code
arc.strength.test Source code
arcs Man page Source code
arcs.rbind Source code
arcs.to.be.added Source code
arcs.to.be.dropped Source code
arcs.to.be.reversed Source code
arcs2amat Source code
arcs2elist Source code
arcs<- Man page
as.bn Man page Source code
as.bn.character Man page Source code
as.bn.fit Man page Source code
as.bn.fit.grain Man page Source code
as.bn.grain Source code
as.bn.graphAM Man page Source code
as.bn.graphNEL Man page Source code
as.character.bn Man page Source code
as.grain Man page Source code
as.grain.bn.fit Man page Source code
as.graphAM Man page Source code
as.graphAM.bn Man page Source code
as.graphAM.bn.fit Man page
as.graphNEL Man page Source code
as.graphNEL.bn Man page Source code
as.graphNEL.bn.fit Man page
asia Man page
averaged.network Man page Source code
averaged.network.backend Source code
bayesian.classifier Source code
bif.check.banner Source code
bif.check.discrete Source code
bif.get.cpt.descriptions Source code
bif.get.cpt.names Source code
bif.get.levels Source code
bif.get.node.descriptions Source code
bif.get.nodes Source code
bif.get.parents Source code
bif.get.probabilities Source code
bif.preparse Source code
bif.write.node Source code
bif.write.probabilities Source code
blacklist Man page Source code
bn class Man page
bn-class Man page
bn.boot Man page Source code
bn.cv Man page Source code
bn.cv.algorithm Source code
bn.cv.structure Source code
bn.fit Man page Source code
bn.fit class Man page
bn.fit plots Man page
bn.fit utilities Man page
bn.fit-class Man page
bn.fit.backend Source code
bn.fit.backend.continuous Source code
bn.fit.backend.discrete Source code
bn.fit.backend.mixedcg Source code
bn.fit.barchart Man page Source code
bn.fit.dnode Man page
bn.fit.dotplot Man page Source code
bn.fit.gnode Man page
bn.fit.histogram Man page Source code
bn.fit.qqplot Man page Source code
bn.fit.xyplot Man page Source code
bn.kcv class Man page
bn.kcv-class Man page
bn.kcv.list class Man page
bn.kcv.list-class Man page
bn.net Man page Source code
bn.recovery Source code
bn.strength Man page
bn.strength class Man page
bn.strength-class Man page
bnlearn Man page Source code
bnlearn-package Man page
boot.strength Man page Source code
bootstrap.backend Source code
build.blacklist Source code
build.whitelist Source code
cache.partial.structure Source code
cache.structure Source code
cextend Man page Source code
cgsd Source code
check.B Source code
check.Rgraphviz Source code
check.alpha Source code
check.amat Source code
check.arcs Source code
check.arcs.against.assumptions Source code
check.bn Source code
check.bn.naive Source code
check.bn.or.fit Source code
check.bn.strength Source code
check.bn.tan Source code
check.bn.vs.data Source code
check.bootsize Source code
check.bootstrap.args Source code
check.cgnode.vs.spec Source code
check.classifier.args Source code
check.classifier.prior Source code
check.cluster Source code
check.colour Source code
check.covariance Source code
check.cpq.args Source code
check.criterion Source code
check.customlist Source code
check.cv.args Source code
check.cv.method Source code
check.data Source code
check.data.frame.finite Source code
check.discretization.args Source code
check.discretization.method Source code
check.dnode.vs.spec Source code
check.experimental Source code
check.fit Source code
check.fit.dnode.spec Source code
check.fit.gnode.spec Source code
check.fit.node.vs.data Source code
check.fit.vs.data Source code
check.fitting.args Source code
check.fitting.method Source code
check.gnode.vs.spec Source code
check.graph.generation.args Source code
check.graph.prior Source code
check.graph.sparsity Source code
check.iss Source code
check.label Source code
check.learning.algorithm Source code
check.learning.algorithm.args Source code
check.logical Source code
check.loss Source code
check.loss.args Source code
check.lty Source code
check.max.iter Source code
check.max.tabu Source code
check.maxp Source code
check.mi.estimator Source code
check.mutilated.evidence Source code
check.nodes Source code
check.penalty Source code
check.perturb Source code
check.phi Source code
check.prediction.method Source code
check.replicates Source code
check.restart Source code
check.score Source code
check.score.args Source code
check.string Source code
check.tabu Source code
check.test Source code
check.threshold Source code
check.unused.args Source code
check.weights Source code
children Man page Source code
children<- Man page
choose.direction Man page Source code
choose.direction.boot Source code
choose.direction.decide Source code
choose.direction.score Source code
choose.direction.test Source code
chow.liu Man page Source code
chow.liu.backend Source code
ci.test Man page Source code
ci.test.character Source code
ci.test.vector Source code
classification.error Source code
clgaussian.test Man page
coef.bn.fit Man page Source code
coef.bn.fit.cgnode Man page
coef.bn.fit.dnode Man page
coef.bn.fit.gnode Man page
coef.bn.fit.onode Man page
compare Man page Source code
compelled.arcs Man page Source code
conditional.probability.query Source code
configs Man page Source code
configurations Source code
constraint-based algorithms Man page
coronary Man page
cpdag Man page Source code
cpdag.arc.backend Source code
cpdag.arc.extension Source code
cpdag.backend Source code
cpdag.extension Source code
cpdist Man page Source code
cpquery Man page Source code
cptattr Source code
crossvalidation Source code
cs.completed.prior Source code
custom.fit Man page Source code
custom.fit.backend Source code
custom.strength Man page Source code
dag2ug.backend Source code
data.type Source code
deal integration Man page
dedup Man page Source code
dedup.backend Source code
degree Man page Source code
degree,bn-method Man page
degree,bn.fit-method Man page
degree,bn.naive-method Man page
degree,bn.tan-method Man page
descendants Man page Source code
directed Man page Source code
directed.arcs Man page Source code
discrete.prediction Source code
discretize Man page Source code
discretize.backend Source code
drop.arc Man page Source code
drop.arc.backend Source code
drop.edge Man page Source code
drop.edge.backend Source code
dsc.check.banner Source code
dsc.check.discrete Source code
dsc.get.levels Source code
dsc.get.node.descriptions Source code
dsc.get.nodes Source code
dsc.get.parents Source code
dsc.get.probabilities Source code
dsc.preparse Source code
dsc.write.node Source code
dsc.write.probabilities Source code
dsep Man page Source code
dseparation Source code
elist2arcs Source code
empty.graph Man page Source code
empty.graph.backend Source code
entropy.loss Source code
equal.backend.bn Source code
equal.backend.fit Source code
explode Source code
fake.markov.blanket Source code
fast.cglm Source code
fast.ia.markov.blanket Source code
fast.iamb Man page Source code
fast.incremental.association Source code
fast.incremental.association.optimized Source code
fast.lm Source code
fcat Source code
fit.dummy.df Source code
fit2arcs Source code
fitted.assignment.backend Source code
fitted.bn.fit Man page Source code
fitted.bn.fit.cgnode Man page
fitted.bn.fit.dnode Man page
fitted.bn.fit.gnode Man page
flatten.2d.table Source code
foreign.get.children Source code
formula.backend Source code
gRain integration Man page
gaussian.prediction Source code
gaussian.test Man page
graph generation utilities Man page
graph integration Man page
graph utilities Man page
graphviz.backend Source code
graphviz.plot Man page Source code
greedy.search Source code
grow.shrink Source code
grow.shrink.optimized Source code
gs Man page Source code
gs.markov.blanket Source code
guess.fitted.class Source code
hailfinder Man page
hamming Man page Source code
hamming.distance Source code
hartemink.discretization Source code
has.path Source code
hc Man page Source code
hill.climbing Source code
hybrid algorithms Man page
hybrid.search Source code
ia.markov.blanket Source code
iamb Man page Source code
ide.cozman.graph Source code
impute Man page Source code
impute.backend.map Source code
impute.backend.parents Source code
in.degree Man page Source code
incident.arcs Man page Source code
incoming.arcs Man page Source code
increment.test.counter Man page Source code
incremental.association Source code
incremental.association.optimized Source code
indep.test Source code
insurance Man page
inter.ia.markov.blanket Source code
inter.iamb Man page Source code
inter.incremental.association Source code
inter.incremental.association.optimized Source code
interval.discretization Source code
is Source code
is.acyclic Source code
is.cauchy.schwarz Source code
is.dag Source code
is.directed Source code
is.legal.arc Source code
is.listed Source code
is.ndmatrix Source code
is.non.negative Source code
is.nonnegative.vector Source code
is.pdag Source code
is.positive Source code
is.positive.integer Source code
is.positive.vector Source code
is.probability Source code
is.probability.vector Source code
is.real.number Source code
is.real.vector Source code
is.row.equal Source code
is.score.decomposable Source code
is.score.equivalent Source code
is.string Source code
is.string.vector Source code
is.symmetric Source code
is.undirected Source code
is.vector Source code
isClusterRunning Source code
kfold.loss.postprocess Source code
lattice.cv.bwplot Source code
lattice.discrete.backend Source code
lattice.gaussian.backend Source code
leaf.nodes Man page Source code
learn.mb Man page Source code
learn.nbr Man page Source code
learning.test Man page
list.cg.illegal.arcs Source code
lizards Man page
local discovery algorithms Man page
logLik.bn Man page Source code
logLik.bn.fit Man page Source code
logic.distribution Source code
logic.sampling Source code
loss.function Source code
map.prediction Source code
marks Man page
match.arcs.and.strengths Source code
match.bn Source code
match.brace Source code
maxmin.pc Source code
maxmin.pc.forward.phase Source code
maxmin.pc.heuristic.optimized Source code
maxmin.pc.optimized Source code
mb Man page Source code
mb.backend Source code
mb.fitted Source code
mb2arcs Source code
mean.bn.strength Man page Source code
mean.square.error Source code
mean.strength Source code
mi.matrix Source code
mi.test Source code
minimal.coefficients Source code
minimal.data.frame Source code
minimal.data.frame.column Source code
minimal.fitted Source code
minimal.residuals Source code
minimal.table Source code
misc utilities Man page
missing.data Source code
mixedcg.prediction Source code
mmhc Man page Source code
mmpc Man page Source code
model string utilities Man page
model2network Man page Source code
model2network.backend Source code
modelstring Man page Source code
modelstring<- Man page
moral Man page Source code
mutilated Man page Source code
mutilated.backend.bn Source code
mutilated.backend.fitted Source code
nSlaves Source code
naive.bayes Man page Source code
naive.bayes.backend Source code
naive.classifier Source code
narcs Man page Source code
narcs.backend Source code
nbr Man page Source code
nbr.backend Source code
nbr2arcs Source code
neighbour Source code
net.check.banner Source code
net.check.discrete Source code
net.get.cpt.descriptions Source code
net.get.cpt.names Source code
net.get.levels Source code
net.get.node.descriptions Source code
net.get.nodes Source code
net.get.parents Source code
net.get.probabilities Source code
net.write.node Source code
net.write.probabilities Source code
nnodes Man page Source code
noattr Source code
node ordering utilities Man page
node.ordering Man page Source code
nodes Man page Source code
nodes,bn-method Man page
nodes,bn.fit-method Man page
nodes,bn.naive-method Man page
nodes,bn.tan-method Man page
nodes<- Man page
nodes<-,bn-method Man page
nodes<-,bn.fit-method Man page
nodes<-,bn.naive-method Man page
nodes<-,bn.tan-method Man page
normalize.cpt Source code
nparams Man page Source code
nparams.backend Source code
nparams.fitted Source code
ntests Man page Source code
obs.per.cell Source code
onLoad Source code
onUnload Source code
ordered.graph Source code
ordering2blacklist Man page Source code
out.degree Man page Source code
outgoing.arcs Man page Source code
parallel integration Man page
parents Man page Source code
parents.backend Source code
parents<- Man page
path Man page Source code
pdag2dag Man page Source code
pdag2dag.backend Source code
pena.backend Source code
per.node.score Source code
perturb.backend Source code
plot.bn Man page Source code
plot.bn.kcv Man page Source code
plot.bn.kcv.list Man page Source code
plot.bn.strength Man page Source code
predict.bn Source code
predict.bn.fit Man page Source code
predict.bn.naive Man page Source code
predict.bn.tan Man page
predictive.correlation Source code
print.bn Source code
print.bn.fit Source code
print.bn.fit.cgnode Source code
print.bn.fit.dnode Source code
print.bn.fit.gnode Source code
print.bn.kcv Source code
print.bn.kcv.list Source code
quantile.discretization Source code
random.graph Man page Source code
random.graph.backend Source code
rbn Man page Source code
rbn.backend Source code
rbn.bn Man page Source code
rbn.bn.fit Man page Source code
rbn.default Source code
read.bif Man page Source code
read.dsc Man page Source code
read.foreign.backend Source code
read.net Man page Source code
reduce.fitted Source code
relabel Source code
relabel.bn Source code
relabel.bn.fit Source code
relevant Man page Source code
reset.test.counter Man page Source code
residuals.bn.fit Man page Source code
residuals.bn.fit.cgnode Man page
residuals.bn.fit.dnode Man page
residuals.bn.fit.gnode Man page
reverse.arc Man page Source code
reverse.arc.backend Source code
reversible.arcs Man page Source code
root.leaf.nodes Source code
root.nodes Man page Source code
roundrobin.test Source code
rsmax2 Man page Source code
sanitize.levels Source code
sanitize.plot.dots Source code
schedule Source code
score Man page Source code
score-based algorithms Man page
score.delta Source code
second.principle Source code
set.arc Man page Source code
set.arc.direction Source code
set.edge Man page Source code
set.edge.backend Source code
shd Man page Source code
si.hiton.pc Man page Source code
si.hiton.pc.backend Source code
si.hiton.pc.backward Source code
si.hiton.pc.heuristic Source code
si.hiton.pc.optimized Source code
sigma Man page Source code
sigma.bn.fit Man page Source code
sigma.bn.fit.cgnode Man page
sigma.bn.fit.gnode Man page
single-node local discovery Man page
skeleton Man page Source code
slaves.setup Source code
smaller Source code
smartSapply Source code
spouses Man page Source code
strength.plot Man page Source code
strength2lwd Source code
structural.hamming.distance Source code
subgraph Man page Source code
subgraph.backend Source code
subsets Source code
tabu Man page Source code
tabu.search Source code
tan.backend Source code
test.counter Man page Source code
threshold Source code
tiers.backend Source code
tiers2blacklist Man page Source code
tree.bayes Man page Source code
tryMethod Source code
underlined Source code
undirected.arcs Man page Source code
unique.arcs Source code
vstruct.apply Source code
vstruct.detect Source code
vstructs Man page Source code
vstructures Source code
wcat Source code
weighting.distribution Source code
weighting.sampling Source code
which.directed Source code
which.listed Source code
which.undirected Source code
whitelist Man page Source code
write.bif Man page Source code
write.dot Man page Source code
write.dot.backend Source code
write.dsc Man page Source code
write.foreign.backend Source code
write.net Man page Source code

Files

inst
inst/CITATION
inst/network.scripts
inst/network.scripts/learning.test.R
inst/network.scripts/clgaussian.test.R
inst/network.scripts/gaussian.test.R
inst/bibtex
inst/bibtex/bnlearn.bib
src
src/per.node.score.c
src/graph.generation.c
src/arcs2amat.c
src/Makevars
src/least.squares.c
src/allocations.c
src/sanitization.c
src/predict.c
src/cg.mutual.information.c
src/shrinkage.c
src/linear.correlation.c
src/common.c
src/rcont2.c
src/acyclic.c
src/rbn.c
src/cache.structure.c
src/tiers.c
src/configurations.c
src/map.lw.c
src/gaussian.loglikelihood.c
src/bn.recovery.c
src/gaussian.monte.carlo.c
src/cextend.c
src/bind.c
src/jonckheere.c
src/cpdist.c
src/htest.c
src/test.counter.c
src/wishart.posterior.c
src/allsubs.test.c
src/hc.cache.lookup.c
src/is.dag.c
src/subsets.c
src/shd.c
src/utest.c
src/filter.arcs.c
src/dedup.c
src/hash.c
src/discrete.tests.c
src/discrete.monte.carlo.c
src/discrete.loglikelihood.c
src/enums.c
src/score.delta.c
src/strings.c
src/graph.priors.c
src/roundrobin.test.c
src/linear.algebra.c
src/data.frame.c
src/df.adjust.c
src/globals.c
src/likelihood.weighting.c
src/bootstrap.c
src/dirichlet.posterior.c
src/which.max.c
src/symmetric.c
src/cg.loglikelihood.c
src/covariance.c
src/mi.matrix.c
src/cg.assumptions.c
src/bayesian.network.c
src/gaussian.tests.c
src/cpdag.c
src/indep.test.c
src/tabu.c
src/fast.lm.c
src/contingency.tables.c
src/arcs2elist.c
src/pdag2dag.c
src/averaging.c
src/path.c
src/loss.c
src/parse.c
src/simulation.c
src/ctest.c
src/nparams.c
src/alpha.star.c
src/is.row.equal.c
src/sampling.c
src/include
src/include/loss.h
src/include/rcore.h
src/include/debugging.h
src/include/dataframe.h
src/include/learning.h
src/include/fitted.h
src/include/tests.h
src/include/graph.h
src/include/scores.h
src/include/bn.h
src/include/covariance.h
src/include/sets.h
src/include/blas.h
src/include/globals.h
src/include/sampling.h
src/include/matrix.h
src/fitted.c
NAMESPACE
data
data/alarm.rda
data/learning.test.rda
data/gaussian.test.rda
data/lizards.rda
data/insurance.rda
data/asia.rda
data/clgaussian.test.rda
data/marks.rda
data/hailfinder.rda
data/coronary.rda
Changelog
R
R/grow-shrink.R
R/fast-iamb.R
R/backend-indep.R
R/frontend-learning.R
R/utils-elist.R
R/utils-cluster.R
R/bootstrap.R
R/inter-iamb.R
R/maxmin-pc.R
R/utils-tests.R
R/frontend-simulation.R
R/lattice.R
R/tabu.R
R/frontend-graph.R
R/impute.R
R/cv.R
R/frontend-score.R
R/frontend-predict.R
R/foreign-read.R
R/graphviz.R
R/hiton-pc.R
R/ci.test.R
R/formula.R
R/predict.R
R/scores.R
R/chow.liu.R
R/incremental-association.R
R/fast.lm.R
R/graph-generation.R
R/cpdag.R
R/frontend-plot.R
R/frontend-print.R
R/foreign-write.R
R/globals.R
R/custom.fit.R
R/utils-sanitization.R
R/simulation.R
R/utils-plot.R
R/frontend-bn.R
R/choose.direction.R
R/frontend-strength.R
R/utils-arcs.R
R/fit.R
R/frontend-packages.R
R/learning-algorithms.R
R/init.R
R/test.R
R/fitted.assignment.R
R/frontend-amat.R
R/utils-amat.R
R/frontend-data.R
R/classifiers.R
R/backend-s4.R
R/nparams.R
R/utils-misc.R
R/frontend-fit.R
R/cpq.R
R/arc.strength.R
R/frontend-lattice.R
R/frontend-foreign.R
R/utils-graph.R
R/data.preprocessing.R
R/arc.operations.R
R/backend-score.R
R/frontend-nodes.R
R/loss.R
R/hill-climbing.R
R/frontend-arcs.R
R/frontend-formula.R
R/utils-print.R
R/frontend-bootstrap.R
R/aracne.R
R/relevant.R
MD5
DESCRIPTION
man
man/arc.strength.Rd
man/bnlearn-package.Rd
man/modelstring.Rd
man/ci.test.Rd
man/bn.kcv.class.Rd
man/score.Rd
man/rbn.Rd
man/foreign.Rd
man/bn.fit.methods.Rd
man/plot.bn.strength.Rd
man/graphviz.plot.Rd
man/gaussian-test.Rd
man/ordering.Rd
man/parallel.Rd
man/relevant.Rd
man/bn.strength-class.Rd
man/mmpc.Rd
man/constraint.Rd
man/naive.bayes.Rd
man/bn.fit.plots.Rd
man/alpha.star.Rd
man/graphgen.Rd
man/dsep.Rd
man/graphpkg.Rd
man/strength.plot.Rd
man/cpquery.Rd
man/marks.Rd
man/hailfinder.Rd
man/lizards.Rd
man/preprocessing.Rd
man/test.counter.Rd
man/choose.direction.Rd
man/hc.Rd
man/learning-test.Rd
man/compare.Rd
man/plot.bn.Rd
man/bn.cv.Rd
man/bn.class.Rd
man/impute.Rd
man/hybrid.Rd
man/coronary.Rd
man/insurance.Rd
man/arcops.Rd
man/cpdag.Rd
man/graph.Rd
man/learn.Rd
man/clgaussian-test.Rd
man/gRain.Rd
man/configs.Rd
man/asia.Rd
man/bnboot.Rd
man/bn.fit.Rd
man/mb.Rd
man/deal.Rd
man/bn.fit.class.Rd
man/alarm.Rd
bnlearn documentation built on May 19, 2017, 11:55 p.m.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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