Man pages for MoTBFs
Learning Hybrid Bayesian Networks using Mixtures of Truncated Basis Functions

asMOPStringParameters to MOP String
asMTEStringConverting MTEs to strings
BICMoTBFComputing the BIC score of an MoTBF function
BICMultiFunctionsBIC score for multiple functions
cleanRemove Objects from Memory
coef.jointmotbfCoefficients of a '"jointmotbf"' object
coef.mopExtract coefficients from MOPs
coef.motbfExtract the coefficients of an MoTBF
coef.mteExtracting the coefficients of an MTE
coercion-motbfCoerce MOTBF Objects to Character or Function
conditionalmotbf.learningLearning conditional MoTBF densities
confusionMatrixConfusion Matrix
dataMiningData pre-processing utilities
derivMOPDerivative of a MOP
derivMoTBFDerivating MoTBFs
derivMTEDerivating MTEs
dimensionFunctionDimension of MoTBFs
discreteStatesFromBNGet the states of all discrete nodes from a MoTFB-BN
ecoliData set Ecoli: Protein Localization Sites
evalJointFunctionEvaluation of joint MoTBFs
eval.motbfEvaluation of MoTBFs
expectedValueMOPExpected Value of an MoP Density Function
expectedValueMTEExpected Value of an MTE Density Function
findConditionalFind Fitted Conditional MoTBFs
generateNormalPriorDataPrior data generation
get_approx_posteriorApproximate inference
getChildParentsFromGraphGet the list of relations in a graph
getCoefficientsGet the coefficients
getDAGRetrieve DAG from BN
getMotbfDimExtract Dimension of MoTBFs
getMotbfVarExtract Variables of MoTBFs
getNonNormalisedRandomMoTBFRamdom MoTBF
getStructureHybrid Bayesian Network structure learning
goodnessMoTBFBNBIC of a hybrid BN
integralJointMoTBFIntegration with MoTBFs
integralMOPIntegration of MOPs
integralMoTBFIntegrating MoTBFs
integralMTEIntegrating MTEs
integrate.motbfIntegrating MoTBFs
is.discreteCheck discreteness of a node
is.motbfCheck MoTBF Classes and Subclasses
is.observedObserved Node
is.rootRoot nodes
jointmotbf.fitJoint MoTBF density learning
jointmotbf.learningJoint MoTBF density learning
LearningHCScore-based hybrid Bayesian Network structure learning
learnMoTBFpriorInformationIncorporating prior knowledge in the estimation process
marginal.jointmotbfMarginalization of MoTBFs
marginalJointMoTBFMarginalization of MoTBFs
mop.learningFitting mixtures of polynomials
MOPTANFitting MoTBFs TAN models
motbf2bnlearnExport discrete motbf to bnlearn format
motbf2grainExport discrete motbf to grain format
motbf.cvCross-validation for MoTBFs
MoTBF-DistributionRandom generation for MoTBF distributions
motbf.fitLearning hybrid BNs with MoTBFs
motbf_typeType of MoTBF
mte.learningFitting mixtures of truncated exponentials.
newRangePriorDataRedefining the Domain
nVariablesNumber of Variables in a Joint Function
plotConditionalPlot Conditional Functions
plot.motbfPlots for "motbf" objects
predict.motbf_fitPredict from an MoTBF Bayesian Network
preprocessedDataData cleaning
printConditionalSummary of conditional MoTBF densities
print.motbfPrint object of class motbf 'print' method for class...
probDiscreteVariableProbability distribution of discrete variables
queryConditional probability queries
r.data.frameInitialize Data Frame
rescale_dataScale data
rescaledFunctionsRescaling MoTBF functions
rnormMultivMultivariate Normal sampling
sample_motbfsGenerate Samples From an MoTBF Bayesian network
subsetDataDataset subsetting
summary.motbfSummarize an '"motbf"' object by describing its main...
thyroidData set Thyroid Disease (thyroid0387)
univMoTBFFitting MoTBFs
UpperBoundLogLikelihoodUpper bound of the loglikelihood
variableEliminationExact inference
variableSelectionVariable selection for MoTBFs
MoTBFs documentation built on Oct. 6, 2026, 1:06 a.m.