Uses of Package
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

Packages that use de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

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.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.motif

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

HomogeneousDiffSM
This is the main class for all homogeneous DifferentiableSequenceScores.

HomogeneousMMDiffSM
This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.

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

HomogeneousDiffSM
This is the main class for all homogeneous DifferentiableSequenceScores.

HomogeneousMM0DiffSM
This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.

HomogeneousMMDiffSM
This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.

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

HomogeneousDiffSM
This is the main class for all homogeneous DifferentiableSequenceScores.