Graphical Independence Networks

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Documentation for package ‘gRain’ version 1.3.11

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Code demos. Use demo() to run them.
• Package NEWS.

Help Pages

absorbEvidence	Set, update and remove evidence.
andtab	Conditional probability tables based on logical dependencies
andtable	Conditional probability tables based on logical dependencies
as.data.frame.grain_ev	Evidence objects
booltab	Conditional probability tables based on logical dependencies
chest	Chest clinic example
chest_cpt	Chest clinic example
compile.cpt_grain	Compile a graphical independence network (a Bayesian network)
compile.grain	Compile a graphical independence network (a Bayesian network)
compile.pot_grain	Compile a graphical independence network (a Bayesian network)
compileCPT	Compile conditional probability tables / cliques potentials.
compilePOT	Compile conditional probability tables / cliques potentials.
components_extract	Extract conditional probabilities and clique potentials from data.
components_gather	Compile conditional probability tables / cliques potentials.
cpt-update	Update components of Bayesian network
cptable	Create conditional probability tables (CPTs)
evidence	Set, update and remove evidence.
evidence.grain	Set, update and remove evidence.
evidence<-	Set, update and remove evidence.
evidence<-.grain	Set, update and remove evidence.
evidence_object	Evidence objects
extractCPT	Extract conditional probabilities and clique potentials from data.
extractMARG	Extract conditional probabilities and clique potentials from data.
extractPOT	Extract conditional probabilities and clique potentials from data.
finding	Set, retrieve, and retract finding in Bayesian network.
generics	gRain generics
getEvidence	Set, update and remove evidence.
getFinding	Set, retrieve, and retract finding in Bayesian network.
grain	Graphical Independence Network
grain-main	Graphical Independence Network
grain-simulate	Simulate from an independence network
grain.CPTspec	Graphical Independence Network
grain.cpt_spec	Graphical Independence Network
grain.dModel	Graphical Independence Network
grain.graphNEL	Graphical Independence Network
grain.pot_spec	Graphical Independence Network
grain_compile	Compile a graphical independence network (a Bayesian network)
grain_evidence	Set, update and remove evidence.
grain_jevidence	Set joint evidence in grain objects
grain_predict	Make predictions from a probabilistic network
grain_propagate	Propagate a graphical independence network (a Bayesian network)
grass	Wet grass example
grass_cpt	Wet grass example
is.null_ev	Evidence objects
isCompiled	gRain generics
isCompiled<-	gRain generics
isPropagated	gRain generics
isPropagated<-	gRain generics
load-save-hugin	Load and save Hugin net files
loadHuginNet	Load and save Hugin net files
logical	Conditional probability tables based on logical dependencies
marg2pot	Extract conditional probabilities and clique potentials from data.
mendel	Mendelian segregation
new_ev	Evidence objects
new_jev	Set joint evidence in grain objects
nodeNames	gRain generics
nodeNames.grain	gRain generics
nodeStates	gRain generics
nodeStates.grain	gRain generics
ortab	Conditional probability tables based on logical dependencies
ortable	Conditional probability tables based on logical dependencies
parse_cpt	Compile conditional probability tables / cliques potentials.
parse_cpt,	Compile conditional probability tables / cliques potentials.
parse_cpt.default	Compile conditional probability tables / cliques potentials.
parse_cpt.xtabs,parse_cpt.cptable_class,	Compile conditional probability tables / cliques potentials.
pEvidence	Set, update and remove evidence.
pFinding	Set, retrieve, and retract finding in Bayesian network.
pot2marg	Extract conditional probabilities and clique potentials from data.
predict.grain	Make predictions from a probabilistic network
print.grain_ev	Evidence objects
print.grain_jev	Set joint evidence in grain objects
propagate.grain	Propagate a graphical independence network (a Bayesian network)
propagateLS	Propagate a graphical independence network (a Bayesian network)
propagateLS__	Propagate a graphical independence network (a Bayesian network)
qgrain	Query a network
querygrain	Query a network
querygrain.grain	Query a network
repeatPattern	Create repeated patterns in Bayesian networks
retractEvidence	Set, update and remove evidence.
retractFinding	Set, retrieve, and retract finding in Bayesian network.
retractJEvidence	Set joint evidence in grain objects
rip.grain	gRain generics
saveHuginNet	Load and save Hugin net files
setCPT	Update components of Bayesian network
setCPT.cpt_grain	Update components of Bayesian network
setdiff_ev	Evidence objects
setEvidence	Set, update and remove evidence.
setFinding	Set, retrieve, and retract finding in Bayesian network.
setJEvidence	Set joint evidence in grain objects
simulate.grain	Simulate from an independence network
subset.grain_ev	Evidence objects
union_ev	Evidence objects
universe	gRain generics
universe.grain	gRain generics
varNames.grainEvidence_	gRain generics
varNames.grain_ev	Evidence objects
vpar.cpt_grain	gRain generics
vpar.cpt_spec	gRain generics