Graphical Independence Networks

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Documentation for package ‘gRain’ version 1.3.12

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

Help Pages

A B C E F G I L M N O P Q R S U V

-- A --

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_evidence	Evidence objects

-- B --

booltab

Conditional probability tables based on logical dependencies

-- C --

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.
compute_p_evidence	Propagate a graphical independence network (a Bayesian network)
cpt	Create conditional probability table CPT.
cptable	Create conditional probability tables (CPTs)

-- E --

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.

-- F --

finding

Set, retrieve, and retract finding in Bayesian network.

-- G --

generics	gRain generics
getEvidence	Set, update and remove evidence.
getFinding	Set, retrieve, and retract finding in Bayesian network.
get_superset_list	Get superset for each element in a list
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_joint_evidence	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

-- I --

is.null_evi	Evidence objects
isCompiled	gRain generics
isCompiled<-	gRain generics
isPropagated	gRain generics
isPropagated<-	gRain generics

-- L --

load-save-hugin	Load and save Hugin net files
loadHuginNet	Load and save Hugin net files
logical	Conditional probability tables based on logical dependencies

-- M --

marg2pot	Extract conditional probabilities and clique potentials from data.
mendel	Mendelian segregation

-- N --

new_evi	Evidence objects
new_jev	Set joint evidence in grain objects
nodeNames	gRain generics
nodeNames.grain	gRain generics
nodeStates	gRain generics
nodeStates.grain	gRain generics

-- O --

ortab	Conditional probability tables based on logical dependencies
ortable	Conditional probability tables based on logical dependencies

-- P --

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_evidence	Evidence objects
print.grain_joint_evidence	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)

-- Q --

qgrain	Query a network
querygrain	Query a network
querygrain.grain	Query a network

-- R --

repeatPattern	Create repeated patterns in Bayesian networks
replace-cpt	Replace CPTs in Bayesian network
replaceCPT	Replace CPTs in Bayesian network
replaceCPT.cpt_grain	Replace CPTs in Bayesian network
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

-- S --

saveHuginNet	Load and save Hugin net files
setdiff_evi	Evidence objects
setEvidence	Set, update and remove evidence.
setFinding	Set, retrieve, and retract finding in Bayesian network.
setJEvidence	Set joint evidence in grain objects
simplify_query	Simplify output query to a Bayesian network
simulate.grain	Simulate from an independence network
subset.grain_evidence	Evidence objects

-- U --

union_evi	Evidence objects
universe	gRain generics
universe.grain	gRain generics

-- V --

varNames.grainEvidence_	gRain generics
varNames.grain_evidence	Evidence objects
vpar.cpt_grain	gRain generics
vpar.cpt_spec	gRain generics