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## Package de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

Provides `DifferentiableStatisticalModel`s that are directed graphical models.

See:
Description

Class Summary
BayesianNetworkDiffSM | This class implements a scoring function that is a moral directed graphical model, i.e. a moral Bayesian network.
BayesianNetworkDiffSMParameterSet | Class for the parameters of a `BayesianNetworkDiffSM`.
BNDiffSMParameter | Class for the parameters of a `BayesianNetworkDiffSM`.
BNDiffSMParameterTree | Class for the tree that represents the context of a `BNDiffSMParameter` in a `BayesianNetworkDiffSM`.
MarkovModelDiffSM | This class implements a `AbstractDifferentiableStatisticalModel` for an inhomogeneous Markov model.

## Package de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels Description

Provides `DifferentiableStatisticalModel`s that are directed graphical models. The currently implemented `BayesianNetworkDiffSM` provides structure learning for inhomogeneous Markov models, Bayesian trees, and permuted Markov models, but can be extended to other graph structures easily using the `Measure` interface. It is important to define only moral Bayesian network structures because of the chosen parameterization.

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