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## Uses of Interface
de.jstacs.sampling.SamplingComponent

Packages that use SamplingComponent
de.jstacs.classifiers.differentiableSequenceScoreBased.sampling | Provides the classes for `AbstractScoreBasedClassifier`s that are based on `SamplingDifferentiableStatisticalModel`s and that sample parameters using the Metropolis-Hastings algorithm.
de.jstacs.sampling | This package contains many classes that can be used while a sampling.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous | This package contains various inhomogeneous models.
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states | The package provides all interfaces and classes for states used in hidden Markov models.
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions |
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete |
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions | The package provides all interfaces and classes for transitions used in hidden Markov models.

Uses of SamplingComponent in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling

Classes in de.jstacs.classifiers.differentiableSequenceScoreBased.sampling that implement SamplingComponent
`protected class` | `SamplingScoreBasedClassifier.DiffSMSamplingComponent` The `SamplingComponent` that handles storing and loading sampled parameters values to and from files.

Uses of SamplingComponent in de.jstacs.sampling

Subinterfaces of SamplingComponent in de.jstacs.sampling
`interface` | `GibbsSamplingModel` This is the interface that any `AbstractTrainableStatisticalModel` has to implement if it should be used in a sampling.
`interface` | `SamplingFromStatistic` This is the interface for sampling based on a sufficient statistic.

Uses of SamplingComponent in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous that implement SamplingComponent
`class` | `FSDAGModelForGibbsSampling` This is the class for a fixed structure directed acyclic graphical model (see `FSDAGTrainSM`) that can be used in a Gibbs sampling.

Uses of SamplingComponent in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states

Subinterfaces of SamplingComponent in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states
`interface` | `SamplingState`

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states that implement SamplingComponent
`class` | `SimpleSamplingState` This class implements a state that can be used for a HMM that obtains its parameters from sampling.

Uses of SamplingComponent in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions

Subinterfaces of SamplingComponent in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions
`interface` | `SamplingEmission`

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions that implement SamplingComponent
`class` | `SilentEmission` This class implements a silent emission which is used to create silent states.

Uses of SamplingComponent in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete that implement SamplingComponent
`class` | `AbstractConditionalDiscreteEmission` The abstract super class of discrete emissions.
`class` | `DiscreteEmission` This class implements a simple discrete emission without any condition.
`class` | `PhyloDiscreteEmission` Phylogenetic discrete emission This class uses a phylogenetic tree to describe multidimensional data It implements Felsensteins model for nucleotide substitution (F81)
`class` | `ReferenceSequenceDiscreteEmission` This class implements a discrete emission that depends on some `ReferenceSequenceAnnotation` at a certain reference position.

Uses of SamplingComponent in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions

Subinterfaces of SamplingComponent in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions
`interface` | `SamplingTransition` This interface declares all method used during a sampling.

Classes in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions that implement SamplingComponent
`class` | `HigherOrderTransition` This class can be used in any `AbstractHMM` allowing to use gradient based or sampling training algorithm.

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