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

as.function.jointmotbfCoerce a '"jointmotbf"' Object to a Function
as.function.motbfCoerce an '"motbf"' object to a Function
asMOPStringParameters to MOP String
asMTEStringConverting MTEs to strings
BICMoTBFComputing the BIC score of an MoTBF function
BICMultiFunctionsBIC score for multiple functions
Class-JointMoTBFClass '"jointmotbf"'
Class-MoTBFClass '"motbf"'
cleanRemove Objects from Memory
coefExpJointCDFDegree Function
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
conditionalmotbf.learningLearning conditional MoTBF densities
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
findConditionalFind fitted conditional MoTBFs
forward_samplingForward Sampling
generateNormalPriorDataPrior data generation
getChildParentsFromGraphGet the list of relations in a graph
getCoefficientsGet the coefficients
getNonNormalisedRandomMoTBFRamdom MoTBF
goodnessDiscreteVariablesBIC scxore and log-likelihood
goodnessMoTBFBNBIC of a hybrid BN
integralJointMoTBFIntegration with MoTBFs
integralMOPIntegration of MOPs
integralMoTBFIntegrating MoTBFs
integralMTEIntegrating MTEs
is.discreteCheck discreteness of a node
is.observedObserved Node
is.rootRoot nodes
jointCDFJoint MoTBFs CDFs
jointmotbf.learningJoint MoTBF density learning
LearningHCScore-based hybrid Bayesian Network structure learning
learnMoTBFpriorInformationIncorporating prior knowledge in the estimation process
marginalJointMoTBFMarginalization of MoTBFs
mop.learningFitting mixtures of polynomials
MoTBF-DistributionRandom generation for MoTBF distributions
MoTBFs_LearningLearning hybrid BNs with MoTBFs
motbf_typeType of MoTBF
mte.learningFitting mixtures of truncated exponentials.
newRangePriorDataRedefining the Domain
nVariablesNumber of Variables in a Joint Function
parentValuesValue of parent nodes
plotConditionalPlot Conditional Functions
plot.jointmotbfBidimensional plots for "jointmotbf" objects
plot.motbfPlots for "motbf" objects
preprocessedDataData cleaning
printBNBN printing
printConditionalSummary of conditional MoTBF densities
printDiscreteBNPrinting discrete Bayesian networks
probDiscreteVariableProbability distribution of discrete variables
r.data.frameData frame initialization for forward sampling
rescaledFunctionsRescaling MoTBF functions
rnormMultivMultivariate Normal sampling
sample_MoTBFsSample generation from conditional MoTBFs
Subclass-MoTBFSubclass '"motbf"' Functions
subsetDataDataset subsetting
summary.jointmotbfSummary of a '"jointmotbf"' object
summary.motbfSummary of an '"motbf"' object
thyroidData set Thyroid Disease (thyroid0387)
univMoTBFFitting MoTBFs
UpperBoundLogLikelihoodUpper bound of the loglikelihood
MoTBFs documentation built on July 1, 2020, 10:36 p.m.