Learning Hybrid Bayesian Networks using Mixtures of Truncated Basis Functions


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Documentation for package ‘MoTBFs’ version 2.0

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

-- A --

as.character.jointmotbf Coerce MOTBF Objects to Character or Function
as.character.motbf Coerce MOTBF Objects to Character or Function
as.function.jointmotbf Coerce MOTBF Objects to Character or Function
as.function.motbf Coerce MOTBF Objects to Character or Function
asMOPString Parameters to MOP String
asMTEString Converting MTEs to strings

-- B --

bestMOP Fitting mixtures of polynomials
bestMTE Fitting mixtures of truncated exponentials.
BiC.MoTBFBN BIC of a hybrid BN
BICMoTBF Computing the BIC score of an MoTBF function
BICMultiFunctions BIC score for multiple functions
BICscoreMoTBF Learning conditional MoTBF densities

-- C --

clean Remove Objects from Memory
coef.jointmotbf Coefficients of a '"jointmotbf"' object
coef.mop Extract coefficients from MOPs
coef.motbf Extract the coefficients of an MoTBF
coef.mte Extracting the coefficients of an MTE
coeffExp Extracting the coefficients of an MTE
coeffMOP Extract coefficients from MOPs
coeffMTE Extracting the coefficients of an MTE
coeffPol Extract coefficients from MOPs
coercion-motbf Coerce MOTBF Objects to Character or Function
conditional Learning conditional MoTBF densities
conditionalMethod Learning conditional MoTBF densities
conditionalmotbf.learning Learning conditional MoTBF densities
confusionMatrix Confusion Matrix
confusionMatrix.motbf_fit_cv Confusion Matrix

-- D --

dataMining Data pre-processing utilities
derivMOP Derivative of a MOP
derivMoTBF Derivating MoTBFs
derivMTE Derivating MTEs
dimensionFunction Dimension of MoTBFs
discreteStatesFromBN Get the states of all discrete nodes from a MoTFB-BN
discreteVariablesStates Data pre-processing utilities
discreteVariables_as.character Data pre-processing utilities
discretizeVariablesEWdis Data pre-processing utilities

-- E --

ecoli Data set Ecoli: Protein Localization Sites
eval.motbf Evaluation of MoTBFs
evalJointFunction Evaluation of joint MoTBFs
expectedValueMOP Expected Value of an MoP Density Function
expectedValueMTE Expected Value of an MTE Density Function

-- F --

findConditional Find Fitted Conditional MoTBFs
fit_tan Fitting MoTBFs TAN models

-- G --

generateNormalPriorData Prior data generation
getChildParentsFromGraph Get the list of relations in a graph
getCoefficients Get the coefficients
getDAG Retrieve DAG from BN
getMotbfDim Extract Dimension of MoTBFs
getMotbfVar Extract Variables of MoTBFs
getNonNormalisedRandomMoTBF Ramdom MoTBF
getStructure Hybrid Bayesian Network structure learning
get_approx_posterior Approximate inference
goodnessMoTBFBN BIC of a hybrid BN

-- I --

integralJointMoTBF Integration with MoTBFs
integralMOP Integration of MOPs
integralMoTBF Integrating MoTBFs
integralMTE Integrating MTEs
integrate.motbf Integrating MoTBFs
inversionMethod Random generation for MoTBF distributions
is.discrete Check discreteness of a node
is.jointmotbf Check MoTBF Classes and Subclasses
is.mop Check MoTBF Classes and Subclasses
is.motbf Check MoTBF Classes and Subclasses
is.motbf_fit Check MoTBF Classes and Subclasses
is.motbf_fit_cv Check MoTBF Classes and Subclasses
is.mte Check MoTBF Classes and Subclasses
is.observed Observed Node
is.root Root nodes
is.univmotbf Check MoTBF Classes and Subclasses

-- J --

jointMoTBF Joint MoTBF density learning
jointmotbf.fit Joint MoTBF density learning
jointmotbf.learning Joint MoTBF density learning

-- L --

learn.tree.Intervals Learning conditional MoTBF densities
LearningHC Score-based hybrid Bayesian Network structure learning
learnMoTBFpriorInformation Incorporating prior knowledge in the estimation process
logLikelihood.MoTBFBN BIC of a hybrid BN

-- M --

marginal.jointmotbf Marginalization of MoTBFs
marginalJointMoTBF Marginalization of MoTBFs
meanMOP Rescaling MoTBF functions
mop.learning Fitting mixtures of polynomials
MOPTAN Fitting MoTBFs TAN models
MoTBF-Distribution Random generation for MoTBF distributions
motbf.cv Cross-validation for MoTBFs
motbf.fit Learning hybrid BNs with MoTBFs
motbf2bnlearn Export discrete motbf to bnlearn format
motbf2grain Export discrete motbf to grain format
MoTBFs_Learning Learning hybrid BNs with MoTBFs
motbf_type Type of MoTBF
mte.learning Fitting mixtures of truncated exponentials.
mutual_information_tan Fitting MoTBFs TAN models

-- N --

newRangePriorData Redefining the Domain
nstates Data pre-processing utilities
nVariables Number of Variables in a Joint Function

-- P --

parametersJointMoTBF Joint MoTBF density learning
plot.jointmotbf Plots for "motbf" objects
plot.motbf Plots for "motbf" objects
plot.motbf.fit.node Plots for "motbf" objects
plot.piecewisemop Plots for "motbf" objects
plot.univmotbf Plots for "motbf" objects
plotConditional Plot Conditional Functions
predict.motbf_fit Predict from an MoTBF Bayesian Network
preprocessedData Data cleaning
print.jointmotbf Print object of class motbf 'print' method for class '"motbf"'.
print.motbf Print object of class motbf 'print' method for class '"motbf"'.
print.motbf.fit.node Print object of class motbf 'print' method for class '"motbf"'.
print.motbf_fit Print object of class motbf 'print' method for class '"motbf"'.
print.motbf_fit_cv Print object of class motbf 'print' method for class '"motbf"'.
print.piecewisemop Print object of class motbf 'print' method for class '"motbf"'.
print.summary.jointmotbf Summarize an '"motbf"' object by describing its main features.
print.summary.piecewisemop Summarize an '"motbf"' object by describing its main features.
print.summary.univmotbf Summarize an '"motbf"' object by describing its main features.
print.univmotbf Print object of class motbf 'print' method for class '"motbf"'.
printConditional Summary of conditional MoTBF densities
probDiscreteVariable Probability distribution of discrete variables

-- Q --

quantileIntervals Data pre-processing utilities
query Conditional probability queries

-- R --

r.data.frame Initialize Data Frame
rescaledFunctions Rescaling MoTBF functions
rescaledMOP Rescaling MoTBF functions
rescaledMoTBFs Rescaling MoTBF functions
rescaledMTE Rescaling MoTBF functions
rescale_data Scale data
rescale_motbf_fit Rescaling MoTBF functions
rMoTBF Random generation for MoTBF distributions
rnormMultiv Multivariate Normal sampling

-- S --

sample_motbfs Generate Samples From an MoTBF Bayesian network
scaleData Data pre-processing utilities
select Learning conditional MoTBF densities
splitdata Dataset subsetting
splitFolds Dataset subsetting
standardizeDataset Data pre-processing utilities
subclass Check MoTBF Classes and Subclasses
subsetData Dataset subsetting
summary.jointmotbf Summarize an '"motbf"' object by describing its main features.
summary.motbf Summarize an '"motbf"' object by describing its main features.
summary.motbf_fit_cv Summarize an '"motbf"' object by describing its main features.
summary.piecewisemop Summarize an '"motbf"' object by describing its main features.
summary.univmotbf Summarize an '"motbf"' object by describing its main features.

-- T --

thyroid Data set Thyroid Disease (thyroid0387)
ToStringRe_MTE Rescaling MoTBF functions
TrainingandTestData Dataset subsetting

-- U --

univMoTBF Fitting MoTBFs
UpperBoundLogLikelihood Upper bound of the loglikelihood

-- V --

variableElimination Exact inference
variableSelection Variable selection for MoTBFs

-- W --

whichDiscrete Data pre-processing utilities