A B C D E F G I J L M N P Q R S T U W
as.character.jointmotbf | Class '"jointmotbf"' |
as.character.motbf | Class '"motbf"' |
as.function.jointmotbf | Coerce a '"jointmotbf"' Object to a Function |
as.function.motbf | Coerce an '"motbf"' Object to a Function |
as.list.jointmotbf | Class '"jointmotbf"' |
as.list.motbf | Class '"motbf"' |
asMOPString | Parameters to MOP String |
asMTEString | Parameters to MTE String |
bestMOP | Fitting Polynomial Models |
bestMTE | Fitting Exponential Models |
BiC.MoTBFBN | BIC of an MoTBF BN |
BICMoTBF | Computing the BIC Score of an MoTBF Function |
BICMultiFunctions | BIC for Multiple Functions |
BICscoreMoTBF | Learning Conditional Functions |
Class-JointMoTBF | Class '"jointmotbf"' |
Class-MoTBF | Class '"motbf"' |
clean | Remove Objects from Memory |
coef.jointmotbf | Extract Coefficients of a '"jointmotbf"' Object |
coef.mop | Extract MOP Coefficients |
coef.motbf | Extract MoTBF Coefficients |
coef.mte | Extract MTE Coefficients |
coefExpJointCDF | Degree Function |
coeffExp | Extract MTE Coefficients |
coeffMOP | Extract MOP Coefficients |
coeffMTE | Extract MTE Coefficients |
coeffPol | Extract MOP Coefficients |
conditional | Learning Conditional Functions |
conditionalMethod | Learning Conditional Functions |
conditionalmotbf.learning | Learning Conditional Functions |
dataMining | Functions to Manipulate a Dataset |
derivMOP | Derivative MOP |
derivMoTBF | Derivative MoTBF |
derivMTE | Derivative MTE |
dimensionFunction | Dimension of Functions |
discreteStatesFromBN | Get the states of all discrete nodes from a MoTFB-BN |
discreteVariablesStates | Functions to Manipulate a Dataset |
discreteVariables_as.character | Functions to Manipulate a Dataset |
discretizeVariablesEWdis | Functions to Manipulate a Dataset |
ecoli | Data set Ecoli: Protein Localization Sites |
evalJointFunction | Evaluate a Joint Function |
findConditional | Find Fitted Conditional MoTBFs |
forward_sampling | Forward Sampling |
generateNormalPriorData | Prior Data |
getBICDiscreteBN | Goodness of discrete probabilities |
getChildParentsFromGraph | Get Relationships in a Network |
getCoefficients | Get the Coefficients |
getlogLikelihoodDiscreteBN | Goodness of discrete probabilities |
getNonNormalisedRandomMoTBF | Ramdom MoTBF |
goodnessDiscreteVariables | Goodness of discrete probabilities |
goodnessMoTBFBN | BIC of an MoTBF BN |
integralJointMoTBF | Integral Joint MoTBF |
integralMOP | Integral MOP |
integralMoTBF | Integral MoTBF |
integralMTE | Integral MTE |
inversionMethod | Random Generation for MoTBFs |
is.discrete | Check discreteness of a node |
is.jointmotbf | Class '"jointmotbf"' |
is.mop | Subclass '"motbf"' Functions |
is.motbf | Class '"motbf"' |
is.mte | Subclass '"motbf"' Functions |
is.observed | Observed Node |
is.root | Root nodes |
jointCDF | Cumulative Joint Distribution |
jointMoTBF | Learning Joint Functions |
jointmotbf | Class '"jointmotbf"' |
jointmotbf.learning | Learning Joint Functions |
learn.tree.Intervals | Learning Conditional Functions |
LearningHC | Learning Hybric Bayesian Networks |
learnMoTBFpriorInformation | Incorporating Prior Knowledge |
logLikelihood.MoTBFBN | BIC of an MoTBF BN |
marginalJointMoTBF | Marginal Joint MoTBF |
meanMOP | Rescales an MoTBF Function |
mop.learning | Fitting Polynomial Models |
motbf | Class '"motbf"' |
MoTBF-Distribution | Random Generation for MoTBFs |
MoTBFs_Learning | Learning MoTBFs in a Network |
motbf_type | Type of MoTBF |
mte.learning | Fitting Exponential Models |
newData | Subset a Dataset |
newRangePriorData | Redefining the Domain |
nstates | Functions to Manipulate a Dataset |
nVariables | Number of Variables in a Joint Function |
parametersJointMoTBF | Learning Joint Functions |
parentValues | Value of Parent Nodes |
plot.jointmotbf | Bidimensional Plots for "jointmotbf" Objects |
plot.motbf | Plots for "motbf" Objects |
plotConditional | Plots for Conditional Functions |
posGrid | Cumulative Joint Distribution |
preprocessedData | Remove Missing Values in a Dataset by Rows |
print.jointmotbf | Class '"jointmotbf"' |
print.motbf | Class '"motbf"' |
print.summary.jointmotbf | Summary of a '"jointmotbf"' Object |
print.summary.motbf | Summary of an '"motbf"' Object |
printBN | Prints BN Results |
printConditional | Prints Conditional Functions |
printDiscreteBN | Prints Discrete Learnings |
probDiscreteVariable | Probabilities Discrete Variables |
quantileIntervals | Functions to Manipulate a Dataset |
r.data.frame | Initialize Data Frame |
rescaledFunctions | Rescales an MoTBF Function |
rescaledMOP | Rescales an MoTBF Function |
rescaledMoTBFs | Rescales an MoTBF Function |
rescaledMTE | Rescales an MoTBF Function |
rMoTBF | Random Generation for MoTBFs |
rnormMultiv | Multivariate Normal Sample |
sample_MoTBFs | Generate Samples From Conditional MoTBFs |
scaleData | Functions to Manipulate a Dataset |
select | Learning Conditional Functions |
splitdata | Subset a Dataset |
standardizeDataset | Functions to Manipulate a Dataset |
subclass | Subclass '"motbf"' Functions |
Subclass-MoTBF | Subclass '"motbf"' Functions |
subsetData | Subset a Dataset |
summary.jointmotbf | Summary of a '"jointmotbf"' Object |
summary.motbf | Summary of an '"motbf"' Object |
thyroid | Data set Thyroid Disease (thyroid0387) |
ToStringRe_MOP | Rescales an MoTBF Function |
ToStringRe_MTE | Rescales an MoTBF Function |
TrainingandTestData | Subset a Dataset |
univMoTBF | Fitting MoTBFs |
UpperBoundLogLikelihood | Upper Bound Loglikelihood |
whichDiscrete | Functions to Manipulate a Dataset |