Function reference • mudim

All functions
`addIntervence(<Model>)`	Add intervence
`anticipate()`	Aniticipating Operator
`as.character(<Distribution>)` `as.character(<Model>)`	Print distribution
`Kappa`	Distribution coins
`compose()` `insert(<Model>)`	Operator of composition
`conditionalIC()`	Conditional multiinformation
`conditionalMI()`	Conditional mutual information
`conditioning()`	Decomposable model conditioning
`copy()`	Copy an entire object
`delete()`	Delete distribution(s) from a model
`dim(<Distribution>)` `dim(<Model>)`	Dimension
`Distribution()`	Probability distribution
`dTable()` `dTable<-`(<Distribution>) `getData(<Distribution>)` `setData(<Distribution>)`	Data table of Distribution
`entropy()`	Entropy
`generalMarginalization()`	General marginalization
`getDistribution()`	Get specific Distribution from a model
`getStructure()` `getVariables(<Model>)`	Model structure
`IC()`	Multiinformation
`info()` `info<-`() `setInfo(<Model>)`	Info
`is.decomposable()`	Decomposability
`is.Distribution()`	Class
`is.empty()`	Is the distribution empty?
`is.reduced()`	Check whether the compositional model structure is reduced
`Kappa`	Distribution Kappa
`KL.divergence()`	Kullback-Leibler divergence
`length(<Model>)`	Length of a compositional model
`loadFromCsv()`	Load Data Matrix from Csv File
`m`	Compositional model
`marginalize()`	Compute marginal Distribution or Model
`MI()`	Mutual information
`Model()`	Create empty Compositional Model
`name()` `name<-`(<Distribution>) `name<-`(<Distribution>) `setName(<Model>)`	Name
`normalize()`	Normalize probability distribution
`perfect()`	Perfectize compositional model
`Pi`	Distribution Pi
`rebuild()`	Recalculate dimension and variables in Distribution or Model
`rebuildFormalRatio()`	Recalculate cache matrix in Distribution
`rebuildFrequency()`	Recalculate Frequency Column in Data Matrix in Distribution
`reduce()`	Reduce compositional model
`reorderRIP()`	RIP-reorder
`replaceDistribution()`	Replace distribution
`saveToCsv()`	Save Distribution as CSV file
`/`(<Distribution>)	Quotient distribution
`splitDistribution()`	Split distribution
`structureEquiv()`	Independence equivalence of structures of respective models
`*`(<Distribution>)	Product distribution
`toDecomposable()`	Transformation into a decomposable model
`toDistribution()`	Convert to Distribution
`toTable()`	Contingency table
`variables()` `variables<-`() `getVariables()` `setVariables()`	Names of random variables
`X`	Dataset X

Reference

All functions

Contents