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## H

hasAnySelfTransitions() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition
hasAnySelfTransitions() - Method in interface de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.Transition
  This method answers the question whether the instance models any self transitions.
hasBeenOptimized - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
  This boolean indicates whether the classifier has been optimized with the method `AbstractClassifier.train(DataSet[])` or the weighted version.
hasBeenOptimized() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
  This method indicates if the classifier has been optimized by a `train`-method.
hasDefault() - Method in class de.jstacs.parameters.AbstractSelectionParameter
  Returns `true`, if this `AbstractSelectionParameter` has a default value.
hasDefault() - Method in class de.jstacs.parameters.MultiSelectionParameter
hasDefault() - Method in class de.jstacs.parameters.SelectionParameter
  Returns `true`, if this `SelectionParameter` has a default value.
hasDefaultOrIsSet() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ArrayParameterSet
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.FileParameter
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.MultiSelectionParameter
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.Parameter
  Returns `true` if the parameter either has a default value or the value was set by the user, `false` otherwise.
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ParameterSet
  Returns `true` if all parameters in this `ParameterSet` are either set by the user or have default values.
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ParameterSetContainer
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.ParameterSetTagger
  This method allows to check whether all tagged parameters that require a value also have some value.
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.RangeParameter
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.SelectionParameter
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.SequenceScoringParameterSet
hasDefaultOrIsSet() - Method in class de.jstacs.parameters.SimpleParameter
hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DGTrainSMParameterSet
hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet
hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.BaumWelchParameterSet
hasDefaultOrIsSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.ViterbiParameterSet
hashCode() - Method in class de.jstacs.data.sequences.Sequence
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.ArbitraryFloatSequence
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.ArbitrarySequence
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.MultiDimensionalSequence
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.Sequence
  This method is used in `Sequence.hashCode()` and the hash code for one specific position.
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.Sequence.RecursiveSequence
hashCodeForPos(int) - Method in class de.jstacs.data.sequences.SimpleDiscreteSequence
hasMoreElements() - Method in class de.jstacs.data.DataSet.ElementEnumerator
hasMoreElements() - Method in class de.jstacs.data.DataSetKMerEnumerator
hasMoreElements() - Method in class de.jstacs.data.DiscreteSequenceEnumerator
hasMoreElements() - Method in class de.jstacs.data.SequenceEnumeration
hasMoreElements() - Method in class de.jstacs.io.InfixStringExtractor
hasMoreElements() - Method in class de.jstacs.io.LimitedStringExtractor
hasMoreElements() - Method in class de.jstacs.io.SimpleStringExtractor
hasMoreElements() - Method in class de.jstacs.io.SparseStringExtractor
hasMoreElements() - Method in class de.jstacs.io.StringExtractor
hasMoreElements() - Method in class de.jstacs.io.SymbolExtractor
hasNext() - Method in class de.jstacs.data.bioJava.SimpleSequenceIterator
hasNext() - Method in class de.jstacs.data.DataSet.ElementEnumerator
hasSampled - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
  This boolean indicates if the parameters for the model were sampled
hasTag(StringBuffer, String, Map<String, String>, Map<String, String>) - Static method in class de.jstacs.io.XMLParser
  This method allows to check whether an XML contains a tagged entry.
helpArray - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LogGenDisMixFunction
  General temporary array
HiddenMotifMixture - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif
  This is the main class that every generative motif discoverer should implement.
HiddenMotifMixture(TrainableStatisticalModel[], boolean[], int, int, boolean, double[], double[], PositionPrior, AbstractMixtureTrainSM.Algorithm, double, TerminationCondition, AbstractMixtureTrainSM.Parameterization, int, int, BurnInTest) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
  Creates a new `HiddenMotifMixture`.
HiddenMotifMixture(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
  The standard constructor for the interface `Storable`.
hiddenParameter - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
  This array contains the hidden parameters of the instance.
hiddenPotential - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
  This array contains the hidden potentials of the instance.
HigherOrderHMM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models
  This class implements a higher order hidden Markov model.
HigherOrderHMM(HMMTrainingParameterSet, String[], Emission[], BasicHigherOrderTransition.AbstractTransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
  This is a convenience constructor.
HigherOrderHMM(HMMTrainingParameterSet, String[], int[], boolean[], Emission[], BasicHigherOrderTransition.AbstractTransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
  This is the main constructor.
HigherOrderHMM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.HigherOrderHMM
  The standard constructor for the interface `Storable`.
HigherOrderHMM.Type - Enum in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models
  This enum defined different types of computations that will be done using the backward algorithm.
HigherOrderTransition - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions
  This class can be used in any `AbstractHMM` allowing to use gradient based or sampling training algorithm.
HigherOrderTransition(boolean[], TransitionElement...) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
  The main constructor.
HigherOrderTransition(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
  The standard constructor for the interface `Storable`.
History - Interface in de.jstacs.motifDiscovery.history
  This interface is used to manage the history of some process.
HMMFactory - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm
  This class allows to create some frequently used HMMs.
HMMFactory() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory
HMMFactory.HMMType - Enum in de.jstacs.sequenceScores.statisticalModels.trainable.hmm
  This enum defines some standard architecture of profile HMMs.
HMMFactory.PseudoTransitionElement - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm
  This class is used as place holder for a later `BasicHigherOrderTransition.AbstractTransitionElement`.
HMMFactory.PseudoTransitionElement(int[], int[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory.PseudoTransitionElement
  This constructor creates an new `HMMFactory.PseudoTransitionElement` without edge weights.
HMMFactory.PseudoTransitionElement(int[], int[], double[], double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory.PseudoTransitionElement
  This constructor creates an new `HMMFactory.PseudoTransitionElement` with specific edge weights.
HMMTrainingParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training
  This class implements an abstract `ParameterSet` that is used for the training of an `AbstractHMM`.
HMMTrainingParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet
  This is the empty constructor that can be used to fill the parameters after creation.
HMMTrainingParameterSet(int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet
  This constructor can be used to create an instance with a specified number of starts.
HMMTrainingParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.training.HMMTrainingParameterSet
  The standard constructor for the interface `Storable`.
HomMMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters
  This class implements a container for all parameters of a homogeneous Markov model.
HomMMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet
  The standard constructor for the interface `Storable`.
HomMMParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet
  An empty constructor.
HomMMParameterSet(AlphabetContainer, double, String, byte) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomMMParameterSet
  Creates a new `HomMMParameterSet` with `AlphabetContainer`, ess (equivalent sample size), description and order of the homogeneous Markov model.
HomogeneousDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
  This is the main class for all homogeneous `DifferentiableSequenceScore`s.
HomogeneousDiffSM(AlphabetContainer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM
  This is the main constructor that creates an instance of a `HomogeneousDiffSM` that models sequences of arbitrary length.
HomogeneousDiffSM(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM
  This is the main constructor that creates an instance of a `HomogeneousDiffSM` that models sequences of a given length.
HomogeneousDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousDiffSM
  This is the constructor for `Storable`.
HomogeneousMM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous
  This class implements homogeneous Markov models (hMM) of arbitrary order.
HomogeneousMM(HomMMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
  Creates a new homogeneous Markov model from a parameter set.
HomogeneousMM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousMM
  The standard constructor for the interface `Storable`.
HomogeneousMM0DiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
  This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.
HomogeneousMM0DiffSM(AlphabetContainer, int, double, boolean, boolean) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
  The main constructor that creates an instance of a homogeneous Markov model of order 0.
HomogeneousMM0DiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMM0DiffSM
  This is the constructor for `Storable`.
HomogeneousMMDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous
  This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.
HomogeneousMMDiffSM(AlphabetContainer, int, double, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
  This is a convenience constructor for creating an instance of a homogeneous Markov model of arbitrary order.
HomogeneousMMDiffSM(AlphabetContainer, int, double, double[], boolean, boolean, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
  This is the main constructor that creates an instance of a homogeneous Markov model of arbitrary order.
HomogeneousMMDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.homogeneous.HomogeneousMMDiffSM
  This is the constructor for `Storable`.
HomogeneousTrainSM - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous
  This class implements homogeneous models of arbitrary order.
HomogeneousTrainSM(HomogeneousTrainSMParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
  Creates a homogeneous model from a parameter set.
HomogeneousTrainSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
  The standard constructor for the interface `Storable`.
HomogeneousTrainSM.HomCondProb - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous
  This class handles the (conditional) probabilities of a homogeneous model in a fast way.
HomogeneousTrainSM.HomCondProb(int[], int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
  The main constructor.
HomogeneousTrainSM.HomCondProb(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
  The standard constructor for the interface `Storable` .
HomogeneousTrainSM.HomCondProb(HomogeneousTrainSM.HomCondProb) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM.HomCondProb
  Creates a new `HomogeneousTrainSM.HomCondProb` instance from a given one.
HomogeneousTrainSMParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters
  This class implements a container for all parameters of any homogeneous model.
HomogeneousTrainSMParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet
  The standard constructor for the interface `Storable`.
HomogeneousTrainSMParameterSet(Class<? extends HomogeneousTrainSM>) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet
  This is the constructor that creates an empty `HomogeneousTrainSMParameterSet` from the class that can be instantiated using this `HomogeneousTrainSMParameterSet`.
HomogeneousTrainSMParameterSet(Class<? extends HomogeneousTrainSM>, AlphabetContainer, double, String, byte) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.parameters.HomogeneousTrainSMParameterSet
  Creates a new `HomogeneousTrainSMParameterSet` with `AlphabetContainer`, ess (equivalent sample size), description and order of the homogeneous Markov model.
hyperParameters - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  The hyperparameters of the prior over the parameters.
hyperParams - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  The hyper-parameters for the prior on the parameters

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