Bayesian network structure learning

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Documentation for package ‘bnlearn’ version 1.8

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

-- --

bnlearn-package Bayesian network structure learning.

-- A --

acyclic Utilities to manipulate graphs
AIC.bn Score of the Bayesian network
alarm ALARM Monitoring System data set
amat Miscellaneous utilities
amat<- Miscellaneous utilities
arc operations Drop, add or set the direction of an arc
arc.strength Measure the strength of the arcs
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.character.bn Build a model string from a Bayesian network and vice versa
asia Asia (synthetic) data set by Lauritzen and Spiegelhalter

-- B --

bn class The bn class structure
bn-class The bn class structure
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.moments Structure Variability of Bayesian networks
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
bn.var.test Structure Variability of Bayesian networks
bnboot Parametric and nonparametric bootstrap of Bayesian networks
bnlearn Bayesian network structure learning.
boot.strength Bootstrap arc strength and direction

-- C --

children Miscellaneous utilities
children<- Miscellaneous utilities
choose.direction Try to infer the direction of an undirected arc
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 learning algorithms
cpdag Find the equivalence class of a Bayesian network

-- D --

dag2ug Utilities to manipulate graphs
deal integration bnlearn - deal package integration
directed Utilities to manipulate graphs
directed.arcs Miscellaneous utilities
drop.arc Drop, add or set the direction of an arc

-- E --

empty.graph Generate an empty or random graph

-- F --

fast.iamb Constraint-based 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
graph generation utilities Generate an empty or random graph
graph utilities Utilities to manipulate graphs
graphviz.plot Advanced Bayesian network plots
gs Constraint-based learning algorithms

-- H --

hailfinder The HailFinder weather forecast system
hc Score-based learning algorithms
hybrid algorithms Hybrid learning algorithms

-- I --

iamb Constraint-based learning algorithms
insurance Insurance evaluation network data set
inter.iamb Constraint-based learning algorithms

-- L --

leaf.nodes Miscellaneous utilities
learning.test Synthetic (discrete) data set to test learning algorithms
lizards Lizards' perching behaviour data set
local discovery algorithms Local discovery learning algorithms
logLik.bn Score of the Bayesian network

-- M --

marks Examination marks data set
mb Miscellaneous utilities
misc utilities Miscellaneous utilities
mmhc Hybrid learning algorithms
mmpc Local discovery 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

-- N --

nbr Miscellaneous utilities
node ordering utilities Partial node ordering utilities
node.ordering Partial node ordering utilities
nodes Miscellaneous utilities
nparams Miscellaneous utilities

-- O --

ordering2blacklist Partial node ordering utilities

-- P --

parents Miscellaneous utilities
parents<- Miscellaneous utilities
path Utilities to manipulate graphs
pdag2dag Utilities to manipulate graphs
plot.bn Plot a Bayesian network

-- R --

random.graph Generate an empty or random graph
rbn Generate random data from a given 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 learning algorithms

-- S --

score Score of the Bayesian network
score-based algorithms Score-based learning algorithms
set.arc Drop, add or set the direction of an arc
snow integration bnlearn - snow package integration
strength.plot Arc strength plot

-- T --

tabu Score-based learning algorithms

-- U --

undirected.arcs Miscellaneous utilities