Bayesian Network Structure Learning from Data with Missing Values

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Documentation for package ‘bnstruct’ version 1.0.15

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

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A B C D E G H I J K L M N O P Q R S T U V W

-- A --

add.observations<-	add further evidence to an existing list of observations of an 'InferenceEngine'.
add.observations<--method	add further evidence to an existing list of observations of an 'InferenceEngine'.
asia	load 'Asia' dataset.
asia_10000	'Asia' dataset.
asia_2_layers	load a two-layers dataset derived from the 'Asia' dataset.

-- B --

belief.propagation	perform belief propagation.
belief.propagation,InferenceEngine	perform belief propagation.
belief.propagation-method	perform belief propagation.
BN	BN class definition.
bn	get the 'BN' object contained in an 'InferenceEngine'.
BN,BN-class	BN class definition.
bn,InferenceEngine	get the 'BN' object contained in an 'InferenceEngine'.
BN-class	BN class definition.
bn-method	get the 'BN' object contained in an 'InferenceEngine'.
bn<-	set the original 'BN' object contained in an 'InferenceEngine'.
bn<--method	set the original 'BN' object contained in an 'InferenceEngine'.
BNDataset	BNDataset class.
BNDataset,BNDataset-class	BNDataset class.
BNDataset-class	BNDataset class.
boot	get selected element of bootstrap list.
boot,BNDataset	get selected element of bootstrap list.
boot-method	get selected element of bootstrap list.
boots	get list of bootstrap samples of a 'BNDataset'.
boots,BNDataset	get list of bootstrap samples of a 'BNDataset'.
boots-method	get list of bootstrap samples of a 'BNDataset'.
boots<-	set list of bootstrap samples of a 'BNDataset'.
boots<--method	set list of bootstrap samples of a 'BNDataset'.
bootstrap	Perform bootstrap.
bootstrap,BNDataset	Perform bootstrap.
bootstrap-method	Perform bootstrap.
build.junction.tree	build a JunctionTree.
build.junction.tree,InferenceEngine	build a JunctionTree.
build.junction.tree-method	build a JunctionTree.

-- C --

child	load 'Child' dataset.
child_NA_5000	'Child' dataset.
complete	Subset a 'BNDataset' to get only complete cases.
complete,BNDataset	Subset a 'BNDataset' to get only complete cases.
complete-method	Subset a 'BNDataset' to get only complete cases.
cpts	get the list of conditional probability tables of a 'BN'.
cpts,BN	get the list of conditional probability tables of a 'BN'.
cpts-method	get the list of conditional probability tables of a 'BN'.
cpts<-	set the list of conditional probability tables of a network.
cpts<--method	set the list of conditional probability tables of a network.

-- D --

dag	get adjacency matrix of a network.
dag,BN	get adjacency matrix of a network.
dag-method	get adjacency matrix of a network.
dag.to.cpdag	convert a DAG to a CPDAG
dag<-	set adjacency matrix of an object.
dag<--method	set adjacency matrix of an object.
data.file	get data file of a 'BNDataset'.
data.file,BNDataset	get data file of a 'BNDataset'.
data.file-method	get data file of a 'BNDataset'.
data.file<-	set data file of a 'BNDataset'.
data.file<--method	set data file of a 'BNDataset'.
discreteness	get status (discrete or continuous) of the variables of an object.
discreteness,BN	get status (discrete or continuous) of the variables of an object.
discreteness,BNDataset	get status (discrete or continuous) of the variables of an object.
discreteness-method	get status (discrete or continuous) of the variables of an object.
discreteness<-	set status (discrete or continuous) of the variables of an object.
discreteness<--method	set status (discrete or continuous) of the variables of an object.

-- E --

edge.dir.wpdag	counts the edges in a WPDAG with their directionality
em	expectation-maximization algorithm.
em,InferenceEngine,BNDataset	expectation-maximization algorithm.
em-method	expectation-maximization algorithm.

-- G --

get.most.probable.values	compute the most probable values to be observed.
get.most.probable.values,BN	compute the most probable values to be observed.
get.most.probable.values,InferenceEngine	compute the most probable values to be observed.
get.most.probable.values-method	compute the most probable values to be observed.

-- H --

has.boots	check whether a 'BNDataset' has bootstrap samples or not.
has.boots,BNDataset	check whether a 'BNDataset' has bootstrap samples or not.
has.boots-method	check whether a 'BNDataset' has bootstrap samples or not.
has.imputed.boots	check whether a 'BNDataset' has bootstrap samples from imputed data or not.
has.imputed.boots,BNDataset	check whether a 'BNDataset' has bootstrap samples from imputed data or not.
has.imputed.boots-method	check whether a 'BNDataset' has bootstrap samples from imputed data or not.
has.imputed.data	check if a BNDataset contains impited data.
has.imputed.data,BNDataset	check if a BNDataset contains impited data.
has.imputed.data-method	check if a BNDataset contains impited data.
has.raw.data	check if a BNDataset contains raw data.
has.raw.data,BNDataset	check if a BNDataset contains raw data.
has.raw.data-method	check if a BNDataset contains raw data.
header.file	get header file of a 'BNDataset'.
header.file,BNDataset	get header file of a 'BNDataset'.
header.file-method	get header file of a 'BNDataset'.
header.file<-	set header file of a 'BNDataset'.
header.file<--method	set header file of a 'BNDataset'.

-- I --

imp.boots	get list of bootstrap samples from imputed data of a 'BNDataset'.
imp.boots,BNDataset	get list of bootstrap samples from imputed data of a 'BNDataset'.
imp.boots-method	get list of bootstrap samples from imputed data of a 'BNDataset'.
imp.boots<-	set list of bootstrap samples from imputed data of a 'BNDataset'.
imp.boots<--method	set list of bootstrap samples from imputed data of a 'BNDataset'.
impute	Impute a 'BNDataset' raw data with missing values.
impute,BNDataset	Impute a 'BNDataset' raw data with missing values.
impute-method	Impute a 'BNDataset' raw data with missing values.
imputed.data	get imputed data of a BNDataset.
imputed.data,BNDataset	get imputed data of a BNDataset.
imputed.data-method	get imputed data of a BNDataset.
imputed.data<-	add imputed data.
imputed.data<--method	add imputed data.
InferenceEngine	InferenceEngine class.
InferenceEngine,InferenceEngine-class	InferenceEngine class.
InferenceEngine-class	InferenceEngine class.
initialize-method	BN class definition.
initialize-method	BNDataset class.
initialize-method	InferenceEngine class.
interventions	get the list of interventions of an 'InferenceEngine'.
interventions,InferenceEngine	get the list of interventions of an 'InferenceEngine'.
interventions-method	get the list of interventions of an 'InferenceEngine'.
interventions<-	set the list of interventions for an 'InferenceEngine'.
interventions<--method	set the list of interventions for an 'InferenceEngine'.

-- J --

jpts	get the list of joint probability tables compiled by an 'InferenceEngine'.
jpts,InferenceEngine	get the list of joint probability tables compiled by an 'InferenceEngine'.
jpts-method	get the list of joint probability tables compiled by an 'InferenceEngine'.
jpts<-	set the list of joint probability tables compiled by an 'InferenceEngine'.
jpts<--method	set the list of joint probability tables compiled by an 'InferenceEngine'.
jt.cliques	get the list of cliques of the junction tree of an 'InferenceEngine'.
jt.cliques,InferenceEngine	get the list of cliques of the junction tree of an 'InferenceEngine'.
jt.cliques-method	get the list of cliques of the junction tree of an 'InferenceEngine'.
jt.cliques<-	set the list of cliques of the junction tree of an 'InferenceEngine'.
jt.cliques<--method	set the list of cliques of the junction tree of an 'InferenceEngine'.
junction.tree	get the junction tree of an 'InferenceEngine'.
junction.tree,InferenceEngine	get the junction tree of an 'InferenceEngine'.
junction.tree-method	get the junction tree of an 'InferenceEngine'.
junction.tree<-	set the junction tree of an 'InferenceEngine'.
junction.tree<--method	set the junction tree of an 'InferenceEngine'.

-- K --

knn.impute

Perform imputation of a data frame using k-NN.

-- L --

layering	return the layering of the nodes.
layering,BN	return the layering of the nodes.
layering-method	return the layering of the nodes.
learn.dynamic.network	learn a dynamic network (structure and parameters) of a BN from a BNDataset.
learn.dynamic.network,BN	learn a dynamic network (structure and parameters) of a BN from a BNDataset.
learn.dynamic.network,BNDataset	learn a dynamic network (structure and parameters) of a BN from a BNDataset.
learn.dynamic.network-method	learn a dynamic network (structure and parameters) of a BN from a BNDataset.
learn.network	learn a network (structure and parameters) of a BN from a BNDataset.
learn.network,BN	learn a network (structure and parameters) of a BN from a BNDataset.
learn.network,BNDataset	learn a network (structure and parameters) of a BN from a BNDataset.
learn.network-method	learn a network (structure and parameters) of a BN from a BNDataset.
learn.params	learn the parameters of a BN.
learn.params,BN,BNDataset	learn the parameters of a BN.
learn.params-method	learn the parameters of a BN.
learn.structure	learn the structure of a network.
learn.structure,BN,BNDataset	learn the structure of a network.
learn.structure-method	learn the structure of a network.

-- M --

marginals	compute the list of inferred marginals of a BN.
marginals,InferenceEngine	compute the list of inferred marginals of a BN.
marginals-method	compute the list of inferred marginals of a BN.

-- N --

name	get name of an object.
name,BN	get name of an object.
name,BNDataset	get name of an object.
name-method	get name of an object.
name<-	set name of an object.
name<--method	set name of an object.
node.sizes	get size of the variables of an object.
node.sizes,BN	get size of the variables of an object.
node.sizes,BNDataset	get size of the variables of an object.
node.sizes-method	get size of the variables of an object.
node.sizes<-	set the size of variables of an object.
node.sizes<--method	set the size of variables of an object.
num.boots	get number of bootstrap samples of a 'BNDataset'.
num.boots,BNDataset	get number of bootstrap samples of a 'BNDataset'.
num.boots-method	get number of bootstrap samples of a 'BNDataset'.
num.boots<-	set number of bootstrap samples of a 'BNDataset'.
num.boots<--method	set number of bootstrap samples of a 'BNDataset'.
num.items	get number of items of a 'BNDataset'.
num.items,BNDataset	get number of items of a 'BNDataset'.
num.items-method	get number of items of a 'BNDataset'.
num.items<-	set number of items of a 'BNDataset'.
num.items<--method	set number of items of a 'BNDataset'.
num.nodes	get number of nodes of an object.
num.nodes,BN	get number of nodes of an object.
num.nodes,InferenceEngine	get number of nodes of an object.
num.nodes-method	get number of nodes of an object.
num.nodes<-	set number of nodes of an object.
num.nodes<--method	set number of nodes of an object.
num.time.steps	get number of time steps observed in a 'BN' or a 'BNDataset'.
num.time.steps,BN	get number of time steps observed in a 'BN' or a 'BNDataset'.
num.time.steps,BNDataset	get number of time steps observed in a 'BN' or a 'BNDataset'.
num.time.steps-method	get number of time steps observed in a 'BN' or a 'BNDataset'.
num.time.steps<-	set number of time steps of a 'BN' or a 'BNDataset'.
num.time.steps<--method	set number of time steps of a 'BN' or a 'BNDataset'.
num.variables	get number of variables of a 'BNDataset'.
num.variables,BNDataset	get number of variables of a 'BNDataset'.
num.variables-method	get number of variables of a 'BNDataset'.
num.variables<-	set number of variables of a 'BNDataset'.
num.variables<--method	set number of variables of a 'BNDataset'.

-- O --

observations	get the list of observations of an 'InferenceEngine'.
observations,InferenceEngine	get the list of observations of an 'InferenceEngine'.
observations-method	get the list of observations of an 'InferenceEngine'.
observations<-	set the list of observations of an 'InferenceEngine'.
observations<--method	set the list of observations of an 'InferenceEngine'.

-- P --

plot	plot a 'BN' as a picture.
plot,BN	plot a 'BN' as a picture.
plot.BN	plot a 'BN' as a picture.
plot.BN,BN	plot a 'BN' as a picture.
print	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.
print,BN	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.
print,BNDataset	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.
print,InferenceEngine	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.
print.BN	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.
print.BN,BN	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.
print.BNDataset	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.
print.BNDataset,BNDataset	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.
print.InferenceEngine	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.
print.InferenceEngine,InferenceEngine	print a 'BN', 'BNDataset' or 'InferenceEngine' to 'stdout'.

-- Q --

quantiles	get the list of quantiles of an object.
quantiles,BN	get the list of quantiles of an object.
quantiles,BNDataset	get the list of quantiles of an object.
quantiles-method	get the list of quantiles of an object.
quantiles<-	set the list of quantiles of an object.
quantiles<--method	set the list of quantiles of an object.

-- R --

raw.data	get raw data of a BNDataset.
raw.data,BNDataset	get raw data of a BNDataset.
raw.data-method	get raw data of a BNDataset.
raw.data<-	add raw data.
raw.data<--method	add raw data.
read.bif	Read a network from a '.bif' file.
read.bif,character	Read a network from a '.bif' file.
read.bif-method	Read a network from a '.bif' file.
read.dataset	Read a dataset from file.
read.dataset,BNDataset,character,character	Read a dataset from file.
read.dataset-method	Read a dataset from file.
read.dsc	Read a network from a '.dsc' file.
read.dsc,character	Read a network from a '.dsc' file.
read.dsc-method	Read a network from a '.dsc' file.
read.net	Read a network from a '.net' file.
read.net,character	Read a network from a '.net' file.
read.net-method	Read a network from a '.net' file.

-- S --

sample.dataset	sample a 'BNDataset' from a network of an inference engine.
sample.dataset,BN	sample a 'BNDataset' from a network of an inference engine.
sample.dataset,InferenceEngine	sample a 'BNDataset' from a network of an inference engine.
sample.dataset-method	sample a 'BNDataset' from a network of an inference engine.
sample.row	sample a row vector of values for a network.
sample.row,BN	sample a row vector of values for a network.
sample.row-method	sample a row vector of values for a network.
save.to.eps	save a 'BN' picture as '.eps' file.
save.to.eps,BN,character	save a 'BN' picture as '.eps' file.
save.to.eps-method	save a 'BN' picture as '.eps' file.
scoring.func	Read the scoring function used to learn the structure of a network.
scoring.func,BN	Read the scoring function used to learn the structure of a network.
scoring.func-method	Read the scoring function used to learn the structure of a network.
scoring.func<-	Set the scoring function used to learn the structure of a network.
scoring.func<--method	Set the scoring function used to learn the structure of a network.
shd	compute the Structural Hamming Distance between two adjacency matrices.
show	Show method for objects.
show-method	Show method for objects.
struct.algo	Read the algorithm used to learn the structure of a network.
struct.algo,BN	Read the algorithm used to learn the structure of a network.
struct.algo-method	Read the algorithm used to learn the structure of a network.
struct.algo<-	Set the algorithm used to learn the structure of a network.
struct.algo<--method	Set the algorithm used to learn the structure of a network.

-- T --

test.updated.bn	check if an updated 'BN' is present in an 'InferenceEngine'.
test.updated.bn,InferenceEngine	check if an updated 'BN' is present in an 'InferenceEngine'.
test.updated.bn-method	check if an updated 'BN' is present in an 'InferenceEngine'.
tune.knn.impute	tune the parameter k of the knn algorithm used in imputation.

-- U --

updated.bn	get the updated 'BN' object contained in an 'InferenceEngine'.
updated.bn,InferenceEngine	get the updated 'BN' object contained in an 'InferenceEngine'.
updated.bn-method	get the updated 'BN' object contained in an 'InferenceEngine'.
updated.bn<-	set the updated 'BN' object contained in an 'InferenceEngine'.
updated.bn<--method	set the updated 'BN' object contained in an 'InferenceEngine'.

-- V --

variables	get variables of an object.
variables,BN	get variables of an object.
variables,BNDataset	get variables of an object.
variables-method	get variables of an object.
variables<-	set variables of an object.
variables<--method	set variables of an object.

-- W --

wpdag	get the WPDAG of an object.
wpdag,BN	get the WPDAG of an object.
wpdag-method	get the WPDAG of an object.
wpdag.from.dag	Initialize a WPDAG from a DAG.
wpdag.from.dag,BN	Initialize a WPDAG from a DAG.
wpdag.from.dag-method	Initialize a WPDAG from a DAG.
wpdag<-	set WPDAG of the object.
wpdag<--method	set WPDAG of the object.
write.dsc	Write a network saving it in a '.dsc' file.
write.dsc,BN	Write a network saving it in a '.dsc' file.
write.dsc-method	Write a network saving it in a '.dsc' file.
write_xgmml	Write a network saving it in an 'XGMML' file.
write_xgmml,BN	Write a network saving it in an 'XGMML' file.
write_xgmml-method	Write a network saving it in an 'XGMML' file.