Uses of Class
de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM

Packages that use HomogeneousMMDiffSM

Package	Description
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.
de.jstacs.sequenceScores.statisticalModels.trainable.hmm	The package provides all interfaces and classes for a hidden Markov model (HMM).

Uses of HomogeneousMMDiffSM in de.jstacs.sequenceScores.statisticalModels.differentiable

Methods in de.jstacs.sequenceScores.statisticalModels.differentiable that return HomogeneousMMDiffSM

Modifier and Type	Method and Description
static HomogeneousMMDiffSM	DifferentiableStatisticalModelFactory.createHomogeneousMarkovModel(AlphabetContainer con, double ess, int order, int priorLength) This method returns a homogeneous Markov model with user-specified order.

Uses of HomogeneousMMDiffSM in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous

Methods in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous that return HomogeneousMMDiffSM

Modifier and Type	Method and Description
HomogeneousMMDiffSM	HomogeneousMMDiffSM.clone()

Uses of HomogeneousMMDiffSM in de.jstacs.sequenceScores.statisticalModels.trainable.hmm

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.hmm that return types with arguments of type HomogeneousMMDiffSM

Modifier and Type	Method and Description
static Pair<AbstractHMM,HomogeneousMMDiffSM>	HMMFactory.parseProfileHMMFromHMMer(Reader hmmReader, StringBuffer consensus, LinkedList<Integer> matchStates, LinkedList<Integer> silentStates) Parses a profile HMM from the textual HMMer representation.