bnlearn: Bayesian Network Structure Learning, Parameter Learning and Inference

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>.

AuthorMarco Scutari
Date of publication2017-02-09 18:20:13
MaintainerMarco Scutari <marco.scutari@gmail.com>
LicenseGPL (>= 2)
Version4.1
http://www.bnlearn.com/

View on CRAN

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

acyclic Man page
AIC.bn Man page
AIC.bn.fit Man page
alarm Man page
all.equal.bn Man page
alpha.star Man page
amat Man page
amat<- Man page
ancestors Man page
aracne Man page
arc operations Man page
arcs Man page
arcs<- Man page
arc.strength Man page
as.bn Man page
as.bn.character Man page
as.bn.fit Man page
as.bn.fit.grain Man page
as.bn.graphAM Man page
as.bn.graphNEL Man page
as.character.bn Man page
as.grain Man page
as.grain.bn.fit Man page
as.graphAM Man page
as.graphAM.bn Man page
as.graphAM.bn.fit Man page
as.graphNEL Man page
as.graphNEL.bn Man page
as.graphNEL.bn.fit Man page
asia Man page
averaged.network Man page
BIC.bn Man page
BIC.bn.fit Man page
blacklist Man page
bn.boot Man page
bn class Man page
bn-class Man page
bn.cv Man page
$<-.bn.fit Man page
bn.fit Man page
bn.fit.barchart Man page
bn.fit class Man page
bn.fit-class Man page
bn.fit.dnode Man page
bn.fit.dotplot Man page
bn.fit.gnode Man page
bn.fit.histogram Man page
bn.fit plots Man page
bn.fit.qqplot Man page
bn.fit utilities Man page
bn.fit.xyplot Man page
bn.kcv class Man page
bn.kcv-class Man page
bn.kcv.list class Man page
bn.kcv.list-class Man page
bnlearn Man page
bnlearn-package Man page
bn.net Man page
bn.strength Man page
bn.strength class Man page
bn.strength-class Man page
boot.strength Man page
cextend Man page
children Man page
children<- Man page
choose.direction Man page
chow.liu Man page
ci.test Man page
clgaussian.test Man page
coef.bn.fit Man page
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
compelled.arcs Man page
configs Man page
constraint-based algorithms Man page
coronary Man page
cpdag Man page
cpdist Man page
cpquery Man page
custom.fit Man page
custom.strength Man page
deal integration Man page
dedup Man page
degree Man page
degree,bn.fit-method Man page
degree,bn-method Man page
degree,bn.naive-method Man page
degree,bn.tan-method Man page
descendants Man page
directed Man page
directed.arcs Man page
discretize Man page
drop.arc Man page
drop.edge Man page
dsep Man page
empty.graph Man page
fast.iamb Man page
fitted.bn.fit Man page
fitted.bn.fit.cgnode Man page
fitted.bn.fit.dnode Man page
fitted.bn.fit.gnode Man page
gaussian.test Man page
gRain integration Man page
graph generation utilities Man page
graph integration Man page
graph utilities Man page
graphviz.plot Man page
gs Man page
hailfinder Man page
hamming Man page
hc Man page
hybrid algorithms Man page
iamb Man page
impute Man page
incident.arcs Man page
incoming.arcs Man page
increment.test.counter Man page
in.degree Man page
insurance Man page
inter.iamb Man page
leaf.nodes Man page
learning.test Man page
learn.mb Man page
learn.nbr Man page
lizards Man page
local discovery algorithms Man page
logLik.bn Man page
logLik.bn.fit Man page
marks Man page
mb Man page
mean.bn.strength Man page
misc utilities Man page
mmhc Man page
mmpc Man page
model2network Man page
modelstring Man page
modelstring<- Man page
model string utilities Man page
moral Man page
mutilated Man page
naive.bayes Man page
narcs Man page
nbr Man page
nnodes Man page
node.ordering Man page
node ordering utilities Man page
nodes Man page
nodes<- Man page
nodes<-,bn.fit-method Man page
nodes,bn.fit-method Man page
nodes<-,bn-method Man page
nodes,bn-method Man page
nodes<-,bn.naive-method Man page
nodes,bn.naive-method Man page
nodes<-,bn.tan-method Man page
nodes,bn.tan-method Man page
nparams Man page
ntests Man page
ordering2blacklist Man page
out.degree Man page
outgoing.arcs Man page
parallel integration Man page
parents Man page
parents<- Man page
path Man page
pdag2dag Man page
plot.bn Man page
plot.bn.kcv Man page
plot.bn.kcv.list Man page
plot.bn.strength Man page
predict.bn.fit Man page
predict.bn.naive Man page
predict.bn.tan Man page
random.graph Man page
rbn Man page
rbn.bn Man page
rbn.bn.fit Man page
read.bif Man page
read.dsc Man page
read.net Man page
relevant Man page
reset.test.counter Man page
residuals.bn.fit Man page
residuals.bn.fit.cgnode Man page
residuals.bn.fit.dnode Man page
residuals.bn.fit.gnode Man page
reverse.arc Man page
reversible.arcs Man page
root.nodes Man page
rsmax2 Man page
score Man page
score-based algorithms Man page
set.arc Man page
set.edge Man page
shd Man page
sigma Man page
sigma.bn.fit Man page
sigma.bn.fit.cgnode Man page
sigma.bn.fit.gnode Man page
si.hiton.pc Man page
single-node local discovery Man page
skeleton Man page
spouses Man page
strength.plot Man page
subgraph Man page
tabu Man page
test.counter Man page
tiers2blacklist Man page
tree.bayes Man page
undirected.arcs Man page
vstructs Man page
whitelist Man page
write.bif Man page
write.dot Man page
write.dsc Man page
write.net Man page

Files

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

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