Learning Hybrid Bayesian Networks using Mixtures of Truncated Basis Functions

Documentation for package ‘MoTBFs’ version 1.2

Help Pages

-- A --

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

-- B --

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

-- C --

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

-- D --

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

-- E --

ecoli	Data set Ecoli: Protein Localization Sites
evalJointFunction	Evaluate a Joint Function

-- F --

findConditional	Find Fitted Conditional MoTBFs
forward_sampling	Forward Sampling

-- G --

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

-- I --

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

-- J --

jointCDF	Cumulative Joint Distribution
jointMoTBF	Learning Joint Functions
jointmotbf	Class '"jointmotbf"'
jointmotbf.learning	Learning Joint Functions

-- L --

learn.tree.Intervals	Learning Conditional Functions
LearningHC	Learning Hybric Bayesian Networks
learnMoTBFpriorInformation	Incorporating Prior Knowledge
logLikelihood.MoTBFBN	BIC of an MoTBF BN

-- M --

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

-- N --

newData	Subset a Dataset
newRangePriorData	Redefining the Domain
nstates	Functions to Manipulate a Dataset
nVariables	Number of Variables in a Joint Function

-- P --

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

-- Q --

Functions to Manipulate a Dataset

-- R --

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

-- S --

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

-- T --

thyroid	Data set Thyroid Disease (thyroid0387)
ToStringRe_MOP	Rescales an MoTBF Function
ToStringRe_MTE	Rescales an MoTBF Function
TrainingandTestData	Subset a Dataset

-- U --

univMoTBF	Fitting MoTBFs
UpperBoundLogLikelihood	Upper Bound Loglikelihood

-- W --

Functions to Manipulate a Dataset