Bayesian Inference for Directed Acyclic Graphs

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Documentation for package ‘BiDAG’ version 2.1.4

• DESCRIPTION file.

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Asia	Asia dataset
Asiamat	Asiamat
bidag2coda	Converting a single BiDAG chain to mcmc object
bidag2codalist	Converting multiple BiDAG chains to mcmc.list
Boston	Boston housing data
compact2full	Deriving an adjecency matrix of a full DBN
compareDAGs	Comparing two graphs
compareDBNs	Comparing two DBNs
connectedSubGraph	Deriving connected subgraph
DAGscore	Calculating the BGe/BDe score of a single DAG
DBNdata	Simulated data set from a 2-step dynamic Bayesian network
DBNmat	An adjacency matrix of a dynamic Bayesian network
DBNscore	Calculating the BGe/BDe score of a single DBN
DBNunrolled	An unrolled adjacency matrix of a dynamic Bayesian network
edgep	Estimating posterior probabilities of single edges
full2compact	Deriving a compact adjacency matrix of a DBN
getDAG	Extracting adjacency matrix (DAG) from MCMC object
getMCMCscore	Extracting score from MCMC object
getRuntime	Extracting runtime
getSpace	Extracting scorespace from MCMC object
getSubGraph	Deriving subgraph
getTrace	Extracting trace from MCMC object
graph2m	Deriving an adjacency matrix of a graph
gsim	A simulated data set from a Gaussian continuous Bayesian network
gsim100	A simulated data set from a Gaussian continuous Bayesian network
gsimmat	An adjacency matrix of a simulated dataset
interactions	interactions dataset
iterativeMCMC	Structure learning with an iterative order MCMC algorithm on an expanded search space
iterativeMCMC class	iterativeMCMC class structure
itercomp	Performance assessment of iterative MCMC scheme against a known Bayesian network
kirc	kirc dataset
kirp	kirp dataset
learnBN	Bayesian network structure learning
m2graph	Deriving a graph from an adjacancy matrix
mapping	mapping dataset
modelp	Estimating a graph corresponding to a posterior probability threshold
orderMCMC	Structure learning with the order MCMC algorithm
orderMCMC class	orderMCMC class structure
partitionMCMC	DAG structure sampling with partition MCMC
partitionMCMC class	partitionMCMC class structure
plot.iterativeMCMC	Structure learning with an iterative order MCMC algorithm on an expanded search space
plot.itercomp	Performance assessment of iterative MCMC scheme against a known Bayesian network
plot.orderMCMC	Structure learning with the order MCMC algorithm
plot.partitionMCMC	DAG structure sampling with partition MCMC
plot.samplecomp	Performance assessment of sampling algorithms against a known Bayesian network
plot2in1	Highlighting similarities between two graphs
plotDBN	Plotting a DBN
plotdiffs	Plotting difference between two graphs
plotdiffsDBN	Plotting difference between two DBNs
plotpcor	Comparing posterior probabilitites of single edges
plotpedges	Plotting posterior probabilities of single edges
print.iterativeMCMC	Structure learning with an iterative order MCMC algorithm on an expanded search space
print.itercomp	Performance assessment of iterative MCMC scheme against a known Bayesian network
print.orderMCMC	Structure learning with the order MCMC algorithm
print.partitionMCMC	DAG structure sampling with partition MCMC
print.samplecomp	Performance assessment of sampling algorithms against a known Bayesian network
print.scoreparameters	Initializing score object
print.scorespace	Prints 'scorespace' object
sampleBN	Bayesian network structure sampling from the posterior distribution
samplecomp	Performance assessment of sampling algorithms against a known Bayesian network
scoreagainstDAG	Calculating the score of a sample against a DAG
scoreagainstDBN	Score against DBN
scoreparameters	Initializing score object
scorespace	Prints 'scorespace' object
scorespace class	scorespace class structure
string2mat	Deriving interactions matrix
summary.iterativeMCMC	Structure learning with an iterative order MCMC algorithm on an expanded search space
summary.itercomp	Performance assessment of iterative MCMC scheme against a known Bayesian network
summary.orderMCMC	Structure learning with the order MCMC algorithm
summary.partitionMCMC	DAG structure sampling with partition MCMC
summary.samplecomp	Performance assessment of sampling algorithms against a known Bayesian network
summary.scoreparameters	Initializing score object
summary.scorespace	Prints 'scorespace' object