Learning Bayesian Networks with Mixed Variables


[Package List] [Top]
addarrow Adding/Turning/Removing arrows
addarrows Add arrows to/from node
addrandomarrow Adding/Turning/Removing random arrows
as.network Greedy search
autosearch Greedy search
banlist Bayesian network data structure
cond Calculate conditional distribution
conditional Calculate conditional distribution
cycletest Test if network contains a cycle
deleterandomarrow Adding/Turning/Removing random arrows
drawnetwork Graphical interface for editing networks
elementin Is a network element in a list of networks?
findex Translation between indices in a multiway array
findleaf Test if network contains a cycle
genlatex From a network family, generate LaTeX output
genpicfile From a network family, generate LaTeX output
heuristic Greedy search
insert Insert/remove an arrow in network
inspectprob Graphical interface for editing networks
jointcont Calculates the joint prior distribution
jointdisc Calculates the joint prior distribution
jointprior Calculates the joint prior distribution
ksl Health and social characteristics
learn Estimation of parameters in the local probability distributions
learnnode Estimation of parameters in the local probability distributions
line Prints a line of symbols
localmaster Local master
makenw Greedy search
makesimprob Make a suggestion for simulation probabilities
maketrylist Creates the full trylist
modelstreng Greedy search
network Bayesian network data structure
networkfamily Generates and learns all networks for a set of variables.
node Representation of nodes
nodes Representation of nodes
numbermixed The number of possible networks
nwequal Test if the graphs of two networks are equal
nwfsort Sorts a list of networks
perturb Perturbs a network
plot.network Bayesian network data structure
plot.networkfamily Generates and learns all networks for a set of variables.
plot.node Representation of nodes
post Calculation of parameter posteriors for continuous node
post0 Calculation of parameter posteriors for continuous node
postc Calculation of parameter posteriors for continuous node
postc0c Calculation of parameter posteriors for continuous node
postcc Calculation of parameter posteriors for continuous node
postdist Calculate point estimate of posterior parameters and create probability distribution
postM Calculation of parameter posteriors for continuous node
print.network Bayesian network data structure
print.networkfamily Generates and learns all networks for a set of variables.
print.node Representation of nodes
prob Representation of nodes
prob.network Bayesian network data structure
prob.node Representation of nodes
rats Weightloss of rats
readnet Reads/saves .net file
removearrow Adding/Turning/Removing arrows
remover Insert/remove an arrow in network
savenet Reads/saves .net file
simulation Simulation of data sets with a given dependency structure
turnarrow Adding/Turning/Removing arrows
turnrandomarrow Adding/Turning/Removing random arrows
udisclik Estimation of parameters in the local probability distributions
unique.networkfamily Makes a network family unique.