Learning Hybrid Bayesian Networks using Mixtures of Truncated Basis Functions

Documentation for package ‘MoTBFs’ version 1.4.1

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	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 --

Class-JointMoTBF	Class '"jointmotbf"'
Class-MoTBF	Class '"motbf"'
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
coefExpJointCDF	Degree Function
coeffExp	Extracting the coefficients of an MTE
coeffMOP	Extract coefficients from MOPs
coeffMTE	Extracting the coefficients of an MTE
coeffPol	Extract coefficients from MOPs
conditional	Learning conditional MoTBF densities
conditionalMethod	Learning conditional MoTBF densities
conditionalmotbf.learning	Learning conditional MoTBF densities

-- 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
evalJointFunction	Evaluation of joint MoTBFs

-- F --

findConditional	Find fitted conditional MoTBFs
forward_sampling	Forward Sampling

-- G --

generateNormalPriorData	Prior data generation
getBICDiscreteBN	BIC scxore and log-likelihood
getChildParentsFromGraph	Get the list of relations in a graph
getCoefficients	Get the coefficients
getlogLikelihoodDiscreteBN	BIC scxore and log-likelihood
getNonNormalisedRandomMoTBF	Ramdom MoTBF
goodnessDiscreteVariables	BIC scxore and log-likelihood
goodnessMoTBFBN	BIC of a hybrid BN

-- I --

integralJointMoTBF	Integration with MoTBFs
integralMOP	Integration of MOPs
integralMoTBF	Integrating MoTBFs
integralMTE	Integrating MTEs
inversionMethod	Random generation for MoTBF distributions
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	Joint MoTBFs CDFs
jointMoTBF	Joint MoTBF density learning
jointmotbf	Class '"jointmotbf"'
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 --

marginalJointMoTBF	Marginalization of MoTBFs
meanMOP	Rescaling MoTBF functions
mop.learning	Fitting mixtures of polynomials
motbf	Class '"motbf"'
MoTBF-Distribution	Random generation for MoTBF distributions
MoTBFs_Learning	Learning hybrid BNs with MoTBFs
motbf_type	Type of MoTBF
mte.learning	Fitting mixtures of truncated exponentials.

-- N --

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

-- P --

parametersJointMoTBF	Joint MoTBF density learning
parentValues	Value of parent nodes
plot.jointmotbf	Bidimensional plots for "jointmotbf" objects
plot.motbf	Plots for "motbf" objects
plotConditional	Plot Conditional Functions
preprocessedData	Data cleaning
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	BN printing
printConditional	Summary of conditional MoTBF densities
printDiscreteBN	Printing discrete Bayesian networks
probDiscreteVariable	Probability distribution of discrete variables

-- Q --

Data pre-processing utilities

-- R --

r.data.frame	Data frame initialization for forward sampling
rescaledFunctions	Rescaling MoTBF functions
rescaledMOP	Rescaling MoTBF functions
rescaledMoTBFs	Rescaling MoTBF functions
rescaledMTE	Rescaling MoTBF functions
rMoTBF	Random generation for MoTBF distributions
rnormMultiv	Multivariate Normal sampling

-- S --

sample_MoTBFs	Sample generation from conditional MoTBFs
scaleData	Data pre-processing utilities
select	Learning conditional MoTBF densities
splitdata	Dataset subsetting
standardizeDataset	Data pre-processing utilities
subclass	Subclass '"motbf"' Functions
Subclass-MoTBF	Subclass '"motbf"' Functions
subsetData	Dataset subsetting
summary.jointmotbf	Summary of a '"jointmotbf"' object
summary.motbf	Summary of an '"motbf"' object

-- T --

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

-- U --

univMoTBF	Fitting MoTBFs
UpperBoundLogLikelihood	Upper bound of the loglikelihood

-- W --

Data pre-processing utilities