Uses of Package
de.jstacs.sequenceScores.statisticalModels

Packages that use de.jstacs.sequenceScores.statisticalModels

de.jstacs.sequenceScores.statisticalModels.differentiable	Provides all DifferentiableStatisticalModels, which can compute the gradient with respect to their parameters for a given input Sequence.
de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels	Provides DifferentiableStatisticalModels that are directed graphical models.
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous	Provides DifferentiableStatisticalModels that are homogeneous, i.e. model probabilities or scores independent of the position within a sequence
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture	Provides DifferentiableSequenceScores that are mixtures of other DifferentiableSequenceScores.
de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif
de.jstacs.sequenceScores.statisticalModels.trainable	Provides all TrainableStatisticalModels, which can be learned from a single DataSet.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous	This package contains various inhomogeneous models.
de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared
de.jstacs.sequenceScores.statisticalModels.trainable.hmm	The package provides all interfaces and classes for a hidden Markov model (HMM).
de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models	The package provides different implementations of hidden Markov models based on AbstractHMM
de.jstacs.sequenceScores.statisticalModels.trainable.mixture	This package is the super package for any mixture model.
de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif
de.jstacs.utils	This package contains a bundle of useful classes and interfaces like ...

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.differentiable

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.differentiable.mixture

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.trainable

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.trainable.discrete

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.shared

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.trainable.hmm

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.trainable.mixture

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.

Classes in de.jstacs.sequenceScores.statisticalModels used by de.jstacs.utils

StatisticalModel
This interface declares methods of a statistical model, i.e., a SequenceScore that defines a proper likelihood over the input Sequences.