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## G

generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.DirichletMRG
generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.EqualParts
generate(int) - Method in class de.jstacs.utils.random.EqualParts
generate(double[], int, int) - Method in class de.jstacs.utils.random.EqualParts
generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.ErlangMRG
generate(int, MRGParams) - Method in class de.jstacs.utils.random.MultivariateRandomGenerator
  Generates a n-dimensional random-array.
generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.MultivariateRandomGenerator
  Generates a n-dimensional random-array as part of the array `d` beginning at `start`.
generate(double[], int, int, MRGParams) - Method in class de.jstacs.utils.random.SoftOneOfN
generate(int) - Method in class de.jstacs.utils.random.SoftOneOfN
generate(double[], int, int) - Method in class de.jstacs.utils.random.SoftOneOfN
GEQ - Static variable in interface de.jstacs.parameters.validation.Constraint
  The condition is greater or equal
get(int) - Method in class de.jstacs.utils.DoubleList
  Returns the element with the specified `index`.
get(int) - Method in class de.jstacs.utils.IntList
  Returns the element with the specified `index`.
getAcceptedMimeType() - Method in class de.jstacs.parameters.FileParameter
  Returns the mime type of the allowed files
getAlignment() - Method in class de.jstacs.algorithms.Alignment
  Computes and returns the alignment of `s1` and `s2` (`Alignment.Alignment(Sequence, Sequence, de.jstacs.algorithms.Alignment.Costs)`)
getAllClassifierAssessmentAssessParameterSets() - Static method in class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
getAllElements() - Method in class de.jstacs.data.Sample
  Returns an array of sequences containing all elements of this Sample.
getAlphabet() - Method in class de.jstacs.parameters.InstanceParameterSet
  Returns the alphabet
getAlphabetAt(int) - Method in class de.jstacs.data.AlphabetContainer
  Returns the underlying alphabet of position `pos`.
getAlphabetContainer() - Method in class de.jstacs.classifier.AbstractClassifier
  This method return the container of alphabets that is used in the classifier.
getAlphabetContainer() - Method in class de.jstacs.data.Sample
  Returns the AlphabetContainer of this Sample.
getAlphabetContainer() - Method in class de.jstacs.data.Sequence
  Return the alphabets used in this sequence.
getAlphabetContainer() - Method in class de.jstacs.models.AbstractModel
getAlphabetContainer() - Method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner
  This method returns the AlphabetContainer of the StructureLearner.
getAlphabetContainer() - Method in interface de.jstacs.models.Model
  Returns the container of alphabets that were used when constructing the model.
getAlphabetContainer() - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
getAlphabetContainer() - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  Returns the `AlphabetContainer` for this `ScoringFunction`.
getAlphabetLengthAt(int) - Method in class de.jstacs.data.AlphabetContainer
  Returns the length of the underlying alphabet of position `pos`.
getAnnotation() - Method in class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
getAnnotation() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
getAnnotation() - Method in class de.jstacs.classifier.assessment.RepeatedHoldOutAssessParameterSet
getAnnotation() - Method in class de.jstacs.classifier.assessment.RepeatedSubSamplingAssessParameterSet
getAnnotation() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
getAnnotation() - Method in class de.jstacs.classifier.MeasureParameters
  Returns the selected parameters and their values as a list of results.
getAnnotation(Sample...) - Static method in class de.jstacs.data.Sample
  Returns the annotation for an array of Samples
getAnnotation() - Method in class de.jstacs.data.Sample
  This method returns some annotation of the sample.
getAnnotation() - Method in class de.jstacs.data.Sequence
  Returns the annotation of the sequence.
getAnnotation() - Method in class de.jstacs.io.StringExtractor
  Returns the annotation of the source.
getAnnotation() - Method in class de.jstacs.results.ListResult
  Returns a reference to the annotation of this `ListResult`
getAnnotations() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
  Returns the additional annotations of this `SequenceAnnotation` as given in the constructor.
getAsymIndex(int, int[], byte) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
getAUC_PR(double[], double[], ArrayList<double[]>) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
  This method computes the area under the precision recall curve.
getAUC_ROC(double[], double[], ArrayList<double[]>) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
  This method computes the area under the receiver operator characteristics curve.
getBest(int, int[], byte) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
  Returns the maximal weight which can be reached for an edge from `k`nodes from the (encoded) set `par` to the node `child`.``
getBooleanFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
  Returns the `boolean` which is the value of the `Parameter par`.
getBorder(double[], double) - Static method in class de.jstacs.classifier.utils.PValueComputation
  This method finds the first index that has a significant score.
getByteFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
  Returns the `byte` which is the value of the `Parameter par`.
getBytesFromFileOnServer(String, RConnection) - Static method in class de.jstacs.utils.RUtils
  This method returns the content of a file on the server as byte array.
getCharacteristics() - Method in class de.jstacs.classifier.AbstractClassifier
  Returns some information characterizing or describing the current instance of the model.
getCharacteristics() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
getCharacteristics() - Method in class de.jstacs.models.AbstractModel
getCharacteristics() - Method in class de.jstacs.models.CompositeModel
getCharacteristics() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
getCharacteristics() - Method in interface de.jstacs.models.Model
  Returns some information characterizing or describing the current instance of the model.
getClassificationRate(Sample[]) - Method in class de.jstacs.classifier.AbstractClassifier
  This method computes the classification rate for a given array of samples.
getClassificationRateFor2Classes(double[], double[]) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
  This method computes the classification rate.
getClassifier() - Method in class de.jstacs.classifier.assessment.ClassifierAssessment
  Returns a deep copy of all classifiers that have been or will be used in this assessment.
getClassifierAnnotation() - Method in class de.jstacs.classifier.AbstractClassifier
  Returns an array of Results of dimension `getNumberOfClasses` that contains information the classifier and for each class.
getClassifierAnnotation() - Method in class de.jstacs.classifier.MappingClassifier
getClassifierAnnotation() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
getClassifierAnnotation() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
getClassifierAnnotation() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier
getClassName() - Method in class de.jstacs.results.StorableResult
  Returns the name of the class of the `Storable` corresponding to the XML-representation stored in this `ObjectResult`.
getClassParams(double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.cll.NormConditionalLogLikelihood
getClassParams(double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.OptimizableFunction
  Returns from the complete vector of parameters those that are for the classes.
getClassWeight(int) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
  Returns the class weight for class `index`.
getClassWeights() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
  Retuns the specific class weights of a AbstractScoreBasedClassifier
getCMI(double[][][][][][], double[][][][][][], double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Computes the conditional mutual information from `fgStats` and `bgStats` counted on sequences with a total weight of `n`.
getCMI(double[][][][], double[][][][], double, double, double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Computes the conditional mutual information from `fgStats` and `bgStats` counted on sequences with a total weight of `nFg` and `nBg`, respectively.
getCode(int, String) - Method in class de.jstacs.data.AlphabetContainer
  Returns the encoded symbol `sym` for position `pos`.
getCode(String) - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
getCollectionOfScales() - Static method in class de.jstacs.parameters.RangeParameter
  Returns a `CollectionsParameter` that allows the user to choose between different scales.
getCombination() - Method in class de.jstacs.models.discrete.inhomogeneous.CombinationIterator
  Returns a clone of the internal combination.
getComment() - Method in class de.jstacs.parameters.CollectionParameter
getComment() - Method in class de.jstacs.parameters.FileParameter
getComment() - Method in class de.jstacs.parameters.Parameter
  Returns a comment on this parameter that tells something about useful values, domains, usage of this parameter, etc.
getComment() - Method in class de.jstacs.parameters.ParameterSetContainer
getComment() - Method in class de.jstacs.parameters.RangeParameter
getComment() - Method in class de.jstacs.parameters.SimpleParameter
getComment() - Method in class de.jstacs.results.Result
  Returns the comment on the result.
getCommentString() - Method in enum de.jstacs.classifier.MeasureParameters.Measure
  Returns a comment on the `MeasureParameters.Measure`
getComplementaryCode(int) - Method in class de.jstacs.data.alphabets.ComplementableDiscreteAlphabet
  This method returns the code of the symbol the is the complement of the symbol encoded by `code`
getComplementaryCode(int) - Method in class de.jstacs.data.alphabets.DNAAlphabet
getComponents() - Method in class de.jstacs.algorithms.graphs.UnionFind
  Returns the connected components of the graph.
getCompositeContainer(int[], int[]) - Method in class de.jstacs.data.AlphabetContainer
  This method returns a container of alphabets e.g. for composite motifs/sequences.
getCompositeSample(int[], int[]) - Method in class de.jstacs.data.Sample
  This method enables you to use only an composite sequences of all elements in the current sample.
getCompositeSequence(AlphabetContainer, int[], int[]) - Method in class de.jstacs.data.Sequence
  This constructor should be used if one wants to create a sample of composite sequences.
getCompositeSequence(int[], int[]) - Method in class de.jstacs.data.Sequence
  This is an very efficient way to create a composite sequence for sequences with a simple AlphabetContainer.
getContent() - Method in class de.jstacs.parameters.FileParameter.FileRepresentation
  Returns the content of the file
getCorrectedPosition(int) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
  Returns the value of the corrected position
getCost() - Method in class de.jstacs.algorithms.Alignment.StringAlignment
  Returns the costs.
getCostFor(Sequence, Sequence, int, int, Alignment.Costs.Direction) - Method in interface de.jstacs.algorithms.Alignment.Costs
  Returns the costs for the alignment if s1(i) and s2(j) coming from `from`.
getCostFor(Sequence, Sequence, int, int, Alignment.Costs.Direction) - Method in class de.jstacs.algorithms.Alignment.SimpleCosts
getCount(int) - Method in class de.jstacs.models.discrete.Constraint
  Returns the current count with index `index`
getCounts() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Returns the current counts for this parameter.
getCurrentParameterSet() - Method in class de.jstacs.data.AlphabetContainer
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.ComplementableDiscreteAlphabet
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
getCurrentParameterSet() - Method in class de.jstacs.data.alphabets.DNAAlphabet
getCurrentParameterSet() - Method in interface de.jstacs.InstantiableFromParameterSet
  Returns the `ParameterSet` that has been used to instantiate the current instance of the implementing class.
getCurrentParameterSet() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getCurrentParameterValues() - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  Returns a double array of dimension `getNumberOfParameters()` containing the current parameter values.
getCurrentParameterValues() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getDataSplitMethod() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
getDataSplitMethod() - Method in class de.jstacs.classifier.assessment.RepeatedHoldOutAssessParameterSet
getDataSplitMethod() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
getDatatype() - Method in class de.jstacs.parameters.CollectionParameter
getDatatype() - Method in class de.jstacs.parameters.FileParameter
getDatatype() - Method in class de.jstacs.parameters.Parameter
  Returns the data type of the parameter
getDatatype() - Method in class de.jstacs.parameters.ParameterSetContainer
getDatatype() - Method in class de.jstacs.parameters.RangeParameter
getDatatype() - Method in class de.jstacs.parameters.SimpleParameter
getDatatype() - Method in class de.jstacs.results.Result
  Returns the datatype of the result.
getDefault() - Method in class de.jstacs.parameters.CollectionParameter
  Returns the index of the default selected value.
getDelim() - Method in class de.jstacs.data.AlphabetContainer
  Returns the delimiter that should be used (for writing e.g. a sequence).
getDepth() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Returns the depth of the tree, i.e. the number of parents of this parameter.
getDescription() - Method in class de.jstacs.io.SubstringFilenameFilter
getDescription() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
  Returns a short description of the model the was given by the user in the parameter set.
getDimension() - Method in class de.jstacs.utils.random.DiMRGParams
getDimension() - Method in class de.jstacs.utils.random.DirichletMRGParams
getDimension() - Method in class de.jstacs.utils.random.ErlangMRGParams
getDimension() - Method in class de.jstacs.utils.random.FastDirichletMRGParams
getDimensionOfScope() - Method in interface de.jstacs.algorithms.optimization.Function
  Returns the dimension of the scope of the function.
getDimensionOfScope() - Method in class de.jstacs.algorithms.optimization.NegativeDifferentiableFunction
getDimensionOfScope() - Method in class de.jstacs.algorithms.optimization.NegativeFunction
getDimensionOfScope() - Method in class de.jstacs.algorithms.optimization.OneDimensionalFunction
getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.cll.NormConditionalLogLikelihood
getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.DoesNothingLogPrior
getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateGaussianLogPrior
getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLaplaceLogPrior
getDimensionOfScope() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior
getDoubleFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
  Returns the `double` which is the value of the `Parameter par`.
getEAR(double[][][][][][], double[][][][][][], double, double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Computes the explaining away residual from `fgStats` and `bgStats` counted on sequences with a total weight of `nFg` and `nBg`, respectively.
getEAR(double[][][][], double[][][][], double, double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Computes the explaining away residual from `fgStats` and `bgStats` counted on sequences with a total weight of `nFg` and `nBg`, respectively.
getEdgeFromIndex(int, int) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
getElapsedTime() - Method in class de.jstacs.utils.RealTime
getElapsedTime() - Method in class de.jstacs.utils.Time
  Returns the elapsed time since invoking the constructor.
getElapsedTime() - Method in class de.jstacs.utils.UserTime
getElement() - Method in class de.jstacs.utils.ComparableElement
  This method returns the element.
getElementAt(int) - Method in class de.jstacs.data.Sample
  This method returns the element with index `i`.
getElementAt(int) - Method in class de.jstacs.data.Sample.WeightedSampleFactory
  Returns the sequence with index `index`.
getElementLength() - Method in class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
getElementLength() - Method in class de.jstacs.data.Sample
  Returns the length of the elements in this Sample.
getElongateCosts() - Method in interface de.jstacs.algorithms.Alignment.Costs
  Returns the costs to elongate a gap by one position
getElongateCosts() - Method in class de.jstacs.algorithms.Alignment.SimpleCosts
getEnd() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
  Returns the end of this `LocatedSequenceAnnotationWithLength`, i.e.
getEndNode() - Method in class de.jstacs.algorithms.graphs.Edge
getEndValue() - Method in class de.jstacs.parameters.RangeParameter
  Returns the last value of a range of parameter values or `null` if no range was specified.
getEntropy(Constraint) - Static method in class de.jstacs.models.discrete.ConstraintManager
  Tries to compute the entropy as exact as possible.
getErrorMessage() - Method in class de.jstacs.parameters.CollectionParameter
getErrorMessage() - Method in class de.jstacs.parameters.FileParameter
getErrorMessage() - Method in class de.jstacs.parameters.Parameter
  If a value could not be set successfully this method returns the corresponding error message.
getErrorMessage() - Method in class de.jstacs.parameters.ParameterSet
  Returns the message of the last error that occurred.
getErrorMessage() - Method in class de.jstacs.parameters.ParameterSetContainer
getErrorMessage() - Method in class de.jstacs.parameters.RangeParameter
getErrorMessage() - Method in class de.jstacs.parameters.SimpleParameter
getErrorMessage() - Method in interface de.jstacs.parameters.validation.Constraint
  Returns the message of the last error (missed constraint) or `null` if the constraint was fulfilled by the last checked value
getErrorMessage() - Method in class de.jstacs.parameters.validation.ConstraintValidator
getErrorMessage() - Method in class de.jstacs.parameters.validation.NumberValidator
getErrorMessage() - Method in interface de.jstacs.parameters.validation.ParameterValidator
  Returns the error message if `checkValue()` returned false.
getErrorMessage() - Method in class de.jstacs.parameters.validation.ReferenceConstraint
getErrorMessage() - Method in class de.jstacs.parameters.validation.SimpleStaticConstraint
getErrorMessage() - Method in class de.jstacs.parameters.validation.StorableValidator
getESS() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
  This method return the ess that is used in this model.
getEss() - Method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner
  This method returns the ESS of the StructureLearner.
getEss() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getEss() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getEss() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getEss() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getEss() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getEss() - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction
getEss() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getEss() - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction
  Returns the equivalent sample size of this model, i.e. the equivalent sample size for the class or component that is represented by this model.
getEss() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getExceptionIfMPNotComputable() - Method in class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
getExpLambda(int) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
  Returns \exp(\lambda_{index}).
getExpValue() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Returns `Math.exp(getValue())`, which is pre-computed.
getExtremum() - Method in class de.jstacs.algorithms.optimization.QuadraticFunction
  This method returns the extremum
getFileContents() - Method in class de.jstacs.parameters.FileParameter
  Returns the content of the file
getFilename() - Method in class de.jstacs.parameters.FileParameter.FileRepresentation
  Returns the filename.
getFirst() - Method in class de.jstacs.algorithms.Alignment.StringAlignment
  Returns the first string.
getFirstParent() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
  Returns the first parent of the random variable of this `ParameterTree` in the topological ordering of the network structure of the enclosing `BayesianNetworkScoringFunction`.
getFloatFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
  Returns the `float` which is the value of the `Parameter par`.
getFPRForSensitivity(double[], double[], double) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
  This method computes the false positive rate (FPR) for a given sensitivity.
getFreq(int) - Method in class de.jstacs.models.discrete.Constraint
  Returns the current frequency with index `index`
getFreq(Sequence, int) - Method in class de.jstacs.models.discrete.Constraint
  This method determines the specific constraint that is fullfilled by the sequence beginning at `start`.
getFreq(int) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
getFunction(Sample[], double[][]) - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
getFunction(Sample[], double[][]) - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
  Returns the function the should be optimized
getFunction(int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This method returns a specific internal function
getFunctions() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This method returns an array of clones of the internal used functions.
getFurtherClassifierInfos() - Method in class de.jstacs.classifier.AbstractClassifier
  This method returns further information of a classifier as a StringBuffer.
getFurtherClassifierInfos() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
getFurtherClassifierInfos() - Method in class de.jstacs.classifier.MappingClassifier
getFurtherClassifierInfos() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
getFurtherClassifierInfos() - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
getFurtherClassifierInfos() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
getFurtherClassifierInfos() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier
getFurtherInformation() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  This method is used in the subclasses to append further information at the xml representation.
getFurtherInformation() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This method is used to append further information of the instance to the xml representation.
getFurtherModelInfos() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
getFurtherModelInfos() - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
getFurtherModelInfos() - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
getGapCostsFor(int) - Method in interface de.jstacs.algorithms.Alignment.Costs
  Returns the costs for a gap of length `length`.
getGapCostsFor(int) - Method in class de.jstacs.algorithms.Alignment.SimpleCosts
getGeneralizedDivergence(double[][], double[][], double) - Static method in class de.jstacs.models.utils.StatisticalTest
  Computes the generalized divergence for two given stochastic matrices over the same domain, i.e. the matrices have to have the same dimensionality.
getGeneralizedDivergence(double[][], double[], double[], double) - Static method in class de.jstacs.models.utils.StatisticalTest
  Computes the generalized divergence for two stochastic matrices over the same domain, i.e. the matrices have to have the same dimensionality.
getGeneralizedDivergence(double[][], double) - Static method in class de.jstacs.models.utils.StatisticalTest
  Computes the generalized divergence for two stochastic matrices over the same domain, i.e. the matrices have to have the same dimensionality.
getHyperparameter(int) - Method in class de.jstacs.utils.random.DiMRGParams
getHyperparameter(int) - Method in class de.jstacs.utils.random.DirichletMRGParams
getHyperparameter(int) - Method in class de.jstacs.utils.random.ErlangMRGParams
getHyperparameter(int) - Method in class de.jstacs.utils.random.FastDirichletMRGParams
getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This method returns the hyperparameter for the hidden parameter with index `index`.
getHyperparameterForHiddenParameter(int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction
getId() - Method in class de.jstacs.parameters.Parameter
  Returns the id of this `Parameter`.
getId() - Method in class de.jstacs.parameters.ParameterSet
  Returns the id of this `ParameterSet`.
getIdentifier() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
  Returns the identifier of this `SequenceAnnotation` as given in the constructor.
getImage(double[][], REnvironment) - Static method in class de.jstacs.models.discrete.inhomogeneous.TwoPointEvaluater
  This method can be used to create an image of mutual information matrix.
getImmutableInstance() - Static method in class de.jstacs.utils.NullProgressUpdater
getIndex(double[], double) - Static method in class de.jstacs.classifier.utils.PValueComputation
  This method searches in `sortedScores` for the index `i` so that `sortedScores[i-1] < myScore <= sortedScores[i]`.
getIndex(double[], double, int) - Static method in class de.jstacs.classifier.utils.PValueComputation
  This method searches in `sortedScores` beginning at `start` for the index `i` so that `sortedScores[i-1] < myScore <= sortedScores[i]`.
getIndex(int) - Method in class de.jstacs.data.Sequence.CompositeSequence
getIndex(int) - Method in class de.jstacs.data.Sequence.SubSequence
getIndex(int) - Method in class de.jstacs.data.sequences.PermutedSequence
getIndex(int) - Method in class de.jstacs.data.sequences.RecursiveSequence
  Return the index in the internal sequence
getIndex(int[]) - Method in class de.jstacs.models.discrete.inhomogeneous.CombinationIterator
  The `combi` has to be sorted.
getIndex(String[], Object[], Comparable, boolean) - Static method in class de.jstacs.parameters.InstanceParameterSet
  This method tries to find the correct name (String) for your choice.
getIndex() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Returns the index of this parameter as defined in the constructor.
getIndexOfMaximalComponentFor(Sequence) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Returns the index `i` of the component with `P(i|s)`maximal.``
getIndexOfMaximalComponentFor(Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  Returns the index of the component that has the greatest impact on the complete score
getIndices(int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This array is used to compute the relative indices of a parameter index.
getInfixSample(int, int) - Method in class de.jstacs.data.Sample
  This method enables you to use only an infix of all elements in the current sample.
getInfos() - Method in class de.jstacs.results.MeanResultSet
  Returns some information for this MeanResultSet.
getInitialClassParam(double) - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
getInitialClassParam(double) - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction
getInitialClassParam(double) - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  Returns the initial class parameter for the class this `ScoringFunction` is responsible for, based on the probability `classProb`.
getInstance() - Method in class de.jstacs.parameters.ParameterSet
  Returns a new instance of the class of `getInstanceClass()` that was created using this `ParameterSet`.
getInstanceClass() - Method in class de.jstacs.parameters.ParameterSet
  Returns the class of the instances that can be constructed using this set.
getInstanceComment() - Method in class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
getInstanceComment() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
getInstanceComment() - Method in class de.jstacs.classifier.assessment.RepeatedHoldOutAssessParameterSet
getInstanceComment() - Method in class de.jstacs.classifier.assessment.RepeatedSubSamplingAssessParameterSet
getInstanceComment() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
getInstanceComment() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet
getInstanceComment() - Method in class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
getInstanceComment() - Method in class de.jstacs.data.AlphabetContainerParameterSet
getInstanceComment() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
getInstanceComment() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet.ContinuousAlphabetParameterSet
getInstanceComment() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet.DiscreteAlphabetParameterSet
getInstanceComment() - Method in class de.jstacs.data.alphabets.DNAAlphabet.DNAAlphabetParameterSet
getInstanceComment() - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet
getInstanceComment() - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.FSDAGMParameterSet
getInstanceComment() - Method in class de.jstacs.parameters.ExpandableParameterSet
getInstanceComment() - Method in class de.jstacs.parameters.ParameterSet
  Returns a comment (a textual description) of the class that can be constructed using this `ParameterSet`.
getInstanceComment() - Method in class de.jstacs.parameters.SimpleParameterSet
getInstanceFromParameterSet(ParameterSet) - Static method in class de.jstacs.io.ParameterSetParser
  Returns an instance of a subclass of `InstantiableFromParameterSet` that can be instantiated by the `ParameterSet pars`.
getInstanceFromParameterSet(ParameterSet, Class) - Static method in class de.jstacs.io.ParameterSetParser
  Returns an instance of a subclass of `InstantiableFromParameterSet` that can be instantiated by the `ParameterSet pars`.
getInstanceName() - Method in class de.jstacs.classifier.AbstractClassifier
  Returns a short description of the classifier.
getInstanceName() - Method in class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
getInstanceName() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
getInstanceName() - Method in class de.jstacs.classifier.assessment.RepeatedHoldOutAssessParameterSet
getInstanceName() - Method in class de.jstacs.classifier.assessment.RepeatedSubSamplingAssessParameterSet
getInstanceName() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
getInstanceName() - Method in class de.jstacs.classifier.MappingClassifier
getInstanceName() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.DoesNothingLogPrior
getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.LogPrior
  Returns a short instance name.
getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateGaussianLogPrior
getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLaplaceLogPrior
getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior
getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
getInstanceName() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifierParameterSet
getInstanceName() - Method in class de.jstacs.data.Alphabet.AlphabetParameterSet
getInstanceName() - Method in class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
getInstanceName() - Method in class de.jstacs.data.AlphabetContainerParameterSet
getInstanceName() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
getInstanceName() - Method in class de.jstacs.models.CompositeModel
getInstanceName() - Method in class de.jstacs.models.discrete.DGMParameterSet
getInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
getInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel
getInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier
getInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
getInstanceName() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
getInstanceName() - Method in class de.jstacs.models.mixture.gibbssampling.BurnInTest
  Returns a short description of the burn-in test.
getInstanceName() - Method in class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
getInstanceName() - Method in interface de.jstacs.models.Model
  Should return a short instance name such as iMM(0), BN(2), ...
getInstanceName() - Method in class de.jstacs.models.UniformModel
getInstanceName() - Method in class de.jstacs.parameters.ExpandableParameterSet
getInstanceName() - Method in class de.jstacs.parameters.ParameterSet
  Returns the name of an instance of the class that can be constructed using this `ParameterSet`.
getInstanceName() - Method in class de.jstacs.parameters.SimpleParameterSet
getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Returns the name of the `Measure` and possibly some additional information about the current instance.
getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
getInstanceName() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
getInstanceName() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getInstanceName() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getInstanceName() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getInstanceName() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getInstanceName() - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction
getInstanceName() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getInstanceName() - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  Returns a short instance name.
getInstanceName() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getIntFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
  Returns the `int` which is the value of the `Parameter par`.
getK() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
getKLDivergence(Model, Model, int) - Static method in class de.jstacs.models.utils.ModelTester
  Returns the Kullback-Leibler-divergence D(p_m1||p_m2).
getKLDivergence(double[]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
  Returns the KL-divergence of the parameters of a PWM to the reference distribution `q`.
getLambda(int) - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
  Returns \lambda_{index}.
getLastScore() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
  Return score that was computed in the last optimization of the parameters.
getLength() - Method in class de.jstacs.classifier.AbstractClassifier
  Returns the length of the sequences this classifier can handle or `0` for sequences of arbitrary length.
getLength() - Method in class de.jstacs.data.Sequence.CompositeSequence
getLength() - Method in class de.jstacs.data.Sequence
  Returns the length of the sequence
getLength() - Method in class de.jstacs.data.Sequence.SubSequence
getLength() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotationWithLength
  Returns the length of this `LocatedSequenceAnnotationWithLength` as given in the constructor.
getLength() - Method in class de.jstacs.data.sequences.ArbitrarySequence
getLength() - Method in class de.jstacs.data.sequences.ByteSequence
getLength() - Method in class de.jstacs.data.sequences.IntSequence
getLength() - Method in class de.jstacs.data.sequences.PermutedSequence
getLength() - Method in class de.jstacs.data.sequences.ShortSequence
getLength() - Method in class de.jstacs.data.sequences.SparseSequence
getLength() - Method in class de.jstacs.models.AbstractModel
getLength() - Method in interface de.jstacs.models.Model
  Returns the length of sequence this model can classify.
getLength() - Method in class de.jstacs.parameters.InstanceParameterSet
  Returns the length of sequences the model can work on
getLength() - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
getLength() - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  Returns the length of this `ScoringFunction`. i.e. the length of the `Sequence`s this `ScoringFunction` can handle.
getLengthOfBurnIn(int) - Method in class de.jstacs.models.mixture.gibbssampling.BurnInTest
  Return the length of the burn in phase of sampling `index`.
getLengthOfBurnIn(int) - Method in class de.jstacs.models.mixture.gibbssampling.SimpleBurnInTest
getLengthOfModels() - Method in class de.jstacs.models.CompositeModel
  This method returns the length of the models in the CompositeModel
getLine(int) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier.DoubleTableResult
  Return the line with index `index` from the table.
getList() - Method in class de.jstacs.parameters.RangeParameter
  Returns a list of all parameter values as a `String` or `null` if no parameter values have been set.
getLnFreq(int) - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb
  Returns the logarithmic frequency.
getLnFreq(Sequence, int) - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb
  Returns the logarithmic frequency.
getLogGammaSum(Constraint, double) - Static method in class de.jstacs.models.discrete.ConstraintManager
  Computes the sum of differences of the logarithmic values of the prior knowlegde and all counts.
getLogLikelihood(Model, Sample) - Static method in class de.jstacs.models.utils.ModelTester
  Returns the loglikelihood of a sample `data` for a given model `m`.
getLogLikelihood(Model, Sample, double[]) - Static method in class de.jstacs.models.utils.ModelTester
  Returns the loglikelihood of a sample `data` for a given model `m`.
getLogPriorTerm() - Method in class de.jstacs.models.CompositeModel
getLogPriorTerm() - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
getLogPriorTerm() - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
getLogPriorTerm() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
getLogPriorTerm() - Method in interface de.jstacs.models.Model
  Returns a value that is proportional to the log of the prior.
getLogPriorTerm() - Method in class de.jstacs.models.UniformModel
getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getLogPriorTerm() - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction
  This method computes a value that is proportional to `getESS()*Math.log( getNormalizationConstant() ) + Math.log( prior ).`
getLogPriorTerm() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getLogPriorTermForComponentProbs() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  This method computes the part of the prior that comes from the component probabilities.
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.AbstractModel
getLogProbFor(Sequence, int) - Method in class de.jstacs.models.AbstractModel
getLogProbFor(Sequence) - Method in class de.jstacs.models.AbstractModel
getLogProbFor(Sample) - Method in class de.jstacs.models.AbstractModel
getLogProbFor(Sample, double[]) - Method in class de.jstacs.models.AbstractModel
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.CompositeModel
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
getLogProbFor(int, Sequence) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Returns the log probability for the sequence and the given component.
getLogProbFor(Sequence, int, int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
getLogProbFor(Sample) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
getLogProbFor(Sequence, int, int) - Method in interface de.jstacs.models.Model
  Returns the logarithm of the probability of the given sequence given the model.
getLogProbFor(Sequence, int) - Method in interface de.jstacs.models.Model
  Returns the logarithm of the probability of the given sequence given the model.
getLogProbFor(Sequence) - Method in interface de.jstacs.models.Model
  Returns the logarithm of the probability of the given sequence given the model.
getLogProbFor(Sample) - Method in interface de.jstacs.models.Model
  This method computes the logarithm of the probabilities of all sequences in the given sample.
getLogProbFor(Sample, double[]) - Method in interface de.jstacs.models.Model
  This method computes and stores the logarithm of the probabilities for any sequence in the sample in the given `double` array.
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Returns the log probability for the sequence and the given component using the current parameter set.
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.models.mixture.MixtureModel
getLogProbUsingCurrentParameterSetFor(int, Sequence, int, int) - Method in class de.jstacs.models.mixture.StrandModel
getLogScore(Sequence) - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
  Returns the log score for the sequence
getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getLogScore(Sequence, int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getLogScore(Sequence, int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getLogScore(Sequence, int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getLogScore(Sequence) - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  Returns the log score for the sequence
getLogScore(Sequence, int) - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  Returns the log score for the sequence
getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getLogScore(Sequence, int) - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
getLogScore(Sequence, int, int) - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
  This method computes the logarithm of the score for a given subsequence.
getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getLogScoreAndPartialDerivation(Sequence, IntList, DoubleList) - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  Returns the log score for the sequence and fills the list with the indices and the partial derivations.
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  Returns the log score for the sequence and fills the list with the indices and the partial derivations.
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getLogScoreAndPartialDerivation(Sequence, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
getLogScoreAndPartialDerivation(Sequence, int, int, IntList, DoubleList) - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
  This method computes the logarithm of the score and the partial derivations for a given subsequence.
getLogSum(double...) - Static method in class de.jstacs.utils.Normalisation
  Returns the log of the sum of values.
getLogSum(int, int, double...) - Static method in class de.jstacs.utils.Normalisation
  Returns the log of the sum of values.
getLongFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
  Returns the `long` which is the value of the `Parameter par`.
getLowerBound() - Method in class de.jstacs.parameters.validation.NumberValidator
  Returns the lower bound of the NumberValidator
getMarginalDistribution(Model, int[]) - Static method in class de.jstacs.models.utils.ModelTester
  This method computes the marginal distribution for any discrete model `m` and all sequences that fulfil the `constraint`, if possible.
getMarginalOrder() - Method in class de.jstacs.models.discrete.Constraint
  Returns the marginal order i.e. the number of used random variables.
getMatrix() - Method in class de.jstacs.classifier.ConfusionMatrix
  This method returns the confusion matrix as a 2D-int-array.
getMax() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
  Returns the maximal value of this alphabet.
getMax(double[][]) - Static method in class de.jstacs.models.discrete.inhomogeneous.TwoPointEvaluater
  This method can be used to determine the maximal value of the matrix.
getMaximalAlphabetLength() - Method in class de.jstacs.data.AlphabetContainer
  Returns the maximal alphabet length of this container.
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
getMaximalEdgeFor(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
  Returns the edge `permute(parents[0],...`
getMaximalElementLength() - Method in class de.jstacs.data.Sample
  Returns the maximal length of an element in this Sample.
getMaximalMarkovOrder() - Method in class de.jstacs.models.AbstractModel
getMaximalMarkovOrder() - Method in class de.jstacs.models.CompositeModel
getMaximalMarkovOrder() - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
getMaximalMarkovOrder() - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel
getMaximalMarkovOrder() - Method in interface de.jstacs.models.Model
  This method returns the maximal used markov order if possible.
getMaximalMarkovOrder() - Method in class de.jstacs.models.UniformModel
getMaximalMarkovOrder() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getMaximalMarkovOrder() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getMaximalMarkovOrder() - Method in class de.jstacs.scoringFunctions.homogeneous.HomogeneousScoringFunction
  Returns the maximal used markov oder.
getMaximalMarkovOrder() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getMaximalSymbolLength() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
getMaxIndex(double[]) - Static method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  Returns the index with maximal value in the array.
getMaxOfCC(double[], double[]) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
  This method computes the maximal correlation coefficient (CC_max).
getMaxOfDeviation(Model, Model, int) - Static method in class de.jstacs.models.utils.ModelTester
  This method computes the maximum deviation between the probabilties for the all sequences of `length` for discrete models `m1` and `m2`.
getMeasure() - Method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair
  This method returns the value of the measure.
getMeasuresForEvaluate() - Static method in class de.jstacs.classifier.AbstractClassifier
  Returns an object of the parameters for the evaluate-method.
getMeasuresForEvaluateAll() - Static method in class de.jstacs.classifier.AbstractClassifier
  Returns an object of the parameters for the evaluateAll-method.
getMI(double[][][][][][], double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Computes the mutual information from `counts` counted on sequences with a total weight of `n`.
getMI(double[][][][], double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Computes the mutual information from `counts` counted on sequences with a total weight of `n`.
getMIInBits(Sample, double[]) - Static method in class de.jstacs.models.discrete.inhomogeneous.TwoPointEvaluater
  This method computes the pairwise mutual information (in bits) between the sequence positions.
getMin() - Method in class de.jstacs.data.Alphabet
  Returns the minimal value.
getMin(int) - Method in class de.jstacs.data.AlphabetContainer
  Returns the min of the underlying alphabet of position `pos`.
getMin() - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
getMin() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
getMinimalAlphabetLength() - Method in class de.jstacs.data.AlphabetContainer
  Returns the minimal alphabet length of this container.
getMinimalElementLength() - Method in class de.jstacs.data.Sample
  Returns the minimal length of an element in this Sample.
getMisclassificationRate() - Method in class de.jstacs.classifier.ConfusionMatrix
  This method returns the misclassification rate.
getModel(int) - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
  Returns a clone of the model for a specified class.
getModel(int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Returns the a deep copy of the i-th model.
getModelInstanceName() - Method in class de.jstacs.models.discrete.inhomogeneous.parameters.BayesianNetworkModelParameterSet
  This method returns a short description of the model.
getModelInstanceName(StructureLearner.ModelType, byte, StructureLearner.LearningType, double) - Static method in class de.jstacs.models.discrete.inhomogeneous.parameters.IDGMParameterSet
  This method returns a short textual representation of the model instance.
getModels() - Method in class de.jstacs.models.CompositeModel
  Returns the a deep copy of the models.
getModels() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Returns the a deep copy of the models.
getMostProbableSequence(Model, int) - Static method in class de.jstacs.models.utils.ModelTester
  Returns one most probable sequence for the discrete model `m`.
getMRG() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  This method creates the multivariate random generator that will be used while initialization.
getMRGParams() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  This method creates the parameters used in a multivariate random generator while initialisation.
getName() - Method in class de.jstacs.parameters.CollectionParameter
getName() - Method in class de.jstacs.parameters.FileParameter
getName() - Method in class de.jstacs.parameters.Parameter
  Returns the name of the parameter
getName() - Method in class de.jstacs.parameters.ParameterSetContainer
getName() - Method in class de.jstacs.parameters.RangeParameter
getName() - Method in class de.jstacs.parameters.SimpleParameter
getName() - Method in class de.jstacs.results.Result
  Returns the name of the result.
getNameOfAlgorithm() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Returns the name of the used algorithm.
getNameOfAssessment() - Method in class de.jstacs.classifier.assessment.ClassifierAssessment
getNameString() - Method in enum de.jstacs.classifier.MeasureParameters.Measure
  Returns the name of the `MeasureParameters.Measure`
getNeededReference() - Method in class de.jstacs.parameters.Parameter
  Returns a reference to a `ParameterSet` whose `ParameterSet.hasDefaultOrIsSet()` method depends on the value of this `Parameter`.
getNeededReference() - Method in class de.jstacs.parameters.RangeParameter
getNeededReferenceId() - Method in class de.jstacs.parameters.Parameter
  Returns the id of the `ParameterSet` that would be returned by `Parameter.getNeededReference()`.
getNewComponentProbs(double[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Estimates the weights.
getNewInstance() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.DoesNothingLogPrior
getNewInstance() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.LogPrior
  This method returns an empty new instance of the current prior.
getNewInstance() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior
getNewInstance() - Method in class de.jstacs.classifier.scoringFunctionBased.logPrior.SimpleGaussianSumLogPrior
getNewParameters(int, double[][], double[]) - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
getNewParameters(int, double[][], double[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  This method trains the internal models on the internal sample and the given weights.
getNewParametersForModel(int, int, int, double[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  This method trains the internal model with index `modelIndex` on the internal sample and the given weights.
getNewStartDistance() - Method in class de.jstacs.algorithms.optimization.ConstantStartDistance
getNewStartDistance() - Method in class de.jstacs.algorithms.optimization.LimitedMedianStartDistance
getNewStartDistance() - Method in interface de.jstacs.algorithms.optimization.StartDistanceForecaster
  This method returns the new positive start distance.
getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Computes sequence weights and returns the score.
getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.models.mixture.MixtureModel
  Computes sequence weights and returns the score.
getNewWeights(double[], double[], double[][]) - Method in class de.jstacs.models.mixture.StrandModel
  Computes sequence weights and returns the score.
getNormalizationConstant() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getNormalizationConstant() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getNormalizationConstant() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
getNormalizationConstant() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getNormalizationConstant() - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction
  Returns the sum of the scores over all sequences of the event space.
getNormalizationConstant() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getNormalizationConstant() - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
getNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
  This method returns the normalization constant for a given sequence length.
getNormalizationConstantForComponent(int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  Computes the normalization constant for the component `i`
getNormalizationConstantForComponent(int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction
getNumberOfClasses() - Method in class de.jstacs.classifier.AbstractClassifier
  Returns the number of classes that can be distinguished.
getNumberOfClasses() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
getNumberOfCombinations(int) - Method in class de.jstacs.models.discrete.inhomogeneous.CombinationIterator
  Returns the number of possible combinations
getNumberOfComponents() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Returns the number of components the are modeled by this AbstractMixtureModel.
getNumberOfComponents() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  Returns the number of different components.
getNumberOfElements() - Method in class de.jstacs.data.Sample
  Returns the number of elements in this Sample.
getNumberOfElements() - Method in class de.jstacs.data.Sample.WeightedSampleFactory
  Returns the number of elements in the internal Sample.
getNumberOfElementsWithLength(int) - Method in class de.jstacs.data.Sample
  Returns the number of overlapping elements that can be extracted.
getNumberOfLines() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier.DoubleTableResult
  Returns the number of lines in this table.
getNumberOfModels() - Method in class de.jstacs.models.CompositeModel
  This method returns the number of models in the CompositeModel
getNumberOfNexts(int) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
  Returns the number of calls to `MultiSelectionCollectionParameter.next()` that can be called before `false` is returned.
getNumberOfNexts(int) - Method in class de.jstacs.parameters.RangeParameter
  Returns the number of calls to `RangeParameter.next()` that can be done, before obtaining `false`.
getNumberOfNodes() - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
  Returns the number of nodes.
getNumberOfParameters() - Method in class de.jstacs.parameters.ArrayParameterSet
getNumberOfParameters() - Method in class de.jstacs.parameters.InstanceParameterSet
getNumberOfParameters() - Method in class de.jstacs.parameters.ParameterSet
  Returns the number of parameters in set
getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getNumberOfParameters() - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  The number of parameters in this scoring function.
getNumberOfParameters() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getNumberOfParents() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
  Returns the number of parents for the random variable of this `ParameterTree` in the network structure of the enclosing `BayesianNetworkScoringFunction`.
getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getNumberOfRecommendedStarts() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
getNumberOfRecommendedStarts() - Method in interface de.jstacs.scoringFunctions.ScoringFunction
  This method return the number of recommended optimization starts.
getNumberOfResults() - Method in class de.jstacs.results.ResultSet
  Returns the number of `Result`s in this `ResultSet`
getNumberOfSpecificConstraints() - Method in class de.jstacs.models.discrete.Constraint
  Returns the number of specific constraint.
getNumberOfStarts() - Method in class de.jstacs.classifier.scoringFunctionBased.cll.NormConditionalLogLikelihood
getNumberOfStarts() - Method in class de.jstacs.classifier.scoringFunctionBased.OptimizableFunction
  Returns the number of starts that should be done for a good optimum.
getNumberOfStrings() - Method in class de.jstacs.io.StringExtractor
  Returns the number of strings
getNumberOfValues() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
getNumberOfValues() - Method in class de.jstacs.parameters.ParameterSet
getNumberOfValues() - Method in class de.jstacs.parameters.ParameterSetContainer
getNumberOfValues() - Method in interface de.jstacs.parameters.RangeIterator
  Returns the number of values in the collection.
getNumberOfValues() - Method in class de.jstacs.parameters.RangeParameter
  Returns the number of values in a list or range of parameter values
getNumericalCharacteristics() - Method in class de.jstacs.classifier.AbstractClassifier
  Returns the subset of numerical values that are also returned by `getCharacteristsics`.
getNumericalCharacteristics() - Method in class de.jstacs.classifier.MappingClassifier
getNumericalCharacteristics() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
getNumericalCharacteristics() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
getNumericalCharacteristics() - Method in class de.jstacs.models.CompositeModel
getNumericalCharacteristics() - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
getNumericalCharacteristics() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
getNumericalCharacteristics() - Method in interface de.jstacs.models.Model
  Returns the subset of numerical values that are also returned by `getCharacteristsics`.
getNumericalCharacteristics() - Method in class de.jstacs.models.UniformModel
getOptimalBranching(double[][], double[][], byte) - Static method in class de.jstacs.algorithms.graphs.Chu_Liu_Edmonds
getOrder() - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
  Returns the order.
getOrder() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
  Returns the order of the Markov model as defined in the constructor
getOutput(byte[], double) - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb
  This method is used to create random sequences.
getOutputStream() - Method in class de.jstacs.utils.SafeOutputStream
  Returns the internal used OutputStream.
getParameterAt(int) - Method in class de.jstacs.parameters.ArrayParameterSet
getParameterAt(int) - Method in class de.jstacs.parameters.InstanceParameterSet
getParameterAt(int) - Method in class de.jstacs.parameters.ParameterSet
  Returns the parameter at position `i`
getParameterFor(Sequence, int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
  Returns the `Parameter` that is responsible for the suffix of sequence `seq` starting at position `start`.
getParametersInCollection() - Method in class de.jstacs.parameters.CollectionParameter
  Returns the possible values in this collection
getParent() - Method in class de.jstacs.parameters.Parameter
  Returns a reference to the `ParameterSet` enclosing this `Parameter`.
getParent() - Method in class de.jstacs.parameters.ParameterSet
  Returns the enclosing `ParameterSetContainer` of this `ParameterSet` or `null` if none exists.
getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Returns the optimal parents for the given data and weights.
getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
getParents(Sample, Sample, double[], double[], int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
getPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getPartialNormalizationConstant(int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getPartialNormalizationConstant(int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getPartialNormalizationConstant(int, int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction
getPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getPartialNormalizationConstant(int) - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction
  Returns the partial normalization constant for the parameter with index `parameterIndex`.
getPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getPartialNormalizationConstant(int) - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
getPartialNormalizationConstant(int, int) - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
  This method returns the partial normalization constant for a given parameter index and sequence length.
getPartialNormalizer() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Returns the partial derivative of the normalization constant with respect to this parameter.
getPartialROC(double[], double[], RangeParameter) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
  This method allows to compute are partial ROC curve.
getPercent() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
getPercents() - Method in class de.jstacs.classifier.assessment.RepeatedHoldOutAssessParameterSet
getPlotCommands(REnvironment, String, AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifier.AbstractScoreBasedClassifier.DoubleTableResult
  This method copies the data to the server side and creates a StringBuffer containing the plot commands.
getPosition() - Method in class de.jstacs.data.sequences.annotation.LocatedSequenceAnnotation
  Returns the position of this `LocatedSequenceAnnotation` on the sequence.
getPosition(int) - Method in class de.jstacs.models.discrete.Constraint
  Returns the position with index `index`
getPosition() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Returns the position of this parameter as defined in the constructor.
getPositionForParameter(int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
  Returns the position in the sequence, the parameter `index` is responsible for.
getPositions() - Method in class de.jstacs.models.discrete.Constraint
  Returns a clone of array of used positions.
getPossibleLength(Model...) - Static method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
  This method returns the possible length of a classifier that would use the given models.
getPossibleLength() - Method in class de.jstacs.data.AlphabetContainer
  Returns the possible length for sequences (, ...) using this container.
getPossibleLength() - Method in class de.jstacs.data.AlphabetContainerParameterSet
  Returns the length of the alphabet that can be instantiated using this set.
getPPVForSensitivity(double[], double[], double) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
  This method computes the positive predictive value (PPV) for a given sensitivity.
getPriorTerm() - Method in class de.jstacs.models.AbstractModel
getPriorTerm() - Method in interface de.jstacs.models.Model
  Returns a value that is proportional to the prior.
getProbFor(Sequence) - Method in class de.jstacs.models.AbstractModel
getProbFor(Sequence, int) - Method in class de.jstacs.models.AbstractModel
getProbFor(Sequence, int, int) - Method in class de.jstacs.models.CompositeModel
getProbFor(Sequence, int, int) - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
getProbFor(Sequence, int, int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
getProbFor(Sequence) - Method in interface de.jstacs.models.Model
  Returns the probability of the given sequence given the model.
getProbFor(Sequence, int) - Method in interface de.jstacs.models.Model
  Returns the probability of the given sequence given the model.
getProbFor(Sequence, int, int) - Method in interface de.jstacs.models.Model
  Returns the probability of the given sequence given the model.
getProbFor(Sequence, int, int) - Method in class de.jstacs.models.UniformModel
getProbsForComponent(Sequence) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  Returns the probabilities for each component
getPseudoCount() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Returns the pseudo count as given in the constructor.
getPValue(Sequence, Sample) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
  Returns the p-value for a sequence `candidate` with respect to a given background sample.
getPValue(Sample, Sample) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
  Returns the p-values for all sequence in `candidates` with respect to a given background sample.
getPValue(double[], double) - Static method in class de.jstacs.classifier.utils.PValueComputation
  This method searches for the insertion point of the score in a given sorted array of scores and returns the p-value for this score.
getPValue(double[], double, int) - Static method in class de.jstacs.classifier.utils.PValueComputation
  This method searches for the insertion point of the score in a given sorted array of scores and returns the p-value for this score.
getPWM() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
  If this `BayesianNetworkScoringFunction` is a PWM, i.e.
getRangedInstance() - Method in class de.jstacs.parameters.CollectionParameter
getRangedInstance() - Method in class de.jstacs.parameters.ParameterSetContainer
getRangedInstance() - Method in interface de.jstacs.parameters.Rangeable
  Returns an instance of `RangeIterator` that has the same properties as the current instance, but accepts a range or list of values.
getRangedInstance() - Method in class de.jstacs.parameters.SimpleParameter
getRawResult() - Method in class de.jstacs.results.ListResult
  Returns a copy of the internal list of `ResultSet`.
getReferenceClass() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
getRepeats() - Method in class de.jstacs.classifier.assessment.RepeatedHoldOutAssessParameterSet
getRepeats() - Method in class de.jstacs.classifier.assessment.RepeatedSubSamplingAssessParameterSet
getRepeats() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
getResult() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier.DoubleTableResult
getResult() - Method in class de.jstacs.results.ImageResult
getResult() - Method in class de.jstacs.results.ListResult
getResult() - Method in class de.jstacs.results.Result
  Returns the value of the result.
getResult() - Method in class de.jstacs.results.SampleResult
getResult() - Method in class de.jstacs.results.SimpleResult
getResult() - Method in class de.jstacs.results.StorableResult
getResultAt(int) - Method in class de.jstacs.results.NumericalResultSet
  Returns the `NumericalResult` number index.
getResultAt(int) - Method in class de.jstacs.results.ResultSet
  Returns `Result` number `index` in this `ResultSet`.
getResultInstance() - Method in class de.jstacs.results.StorableResult
  Returns the instance of the `Storable` that is the result of this `ObjectResult`
getResults(Sample[], MeasureParameters, boolean, boolean) - Method in class de.jstacs.classifier.AbstractClassifier
  This method computes the results for any evaluation of the classifier.
getResults(Sample[], MeasureParameters, boolean, boolean) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
getResults() - Method in class de.jstacs.results.ResultSet
  Returns all internal results.
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
getRootValue(int) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
  Returns the value for `child` as root.
getSample() - Method in class de.jstacs.data.Sample.WeightedSampleFactory
  Returns the sample, where each sequence occurs only once
getScale() - Method in class de.jstacs.parameters.RangeParameter
  Returns a description of the the scale of a range of parameter values.
getScatterplot(AbstractScoreBasedClassifier, AbstractScoreBasedClassifier, Sample, Sample, REnvironment, boolean) - Static method in class de.jstacs.classifier.utils.ClassificationVisualizer
  This method returns an ImageResult containing a scatter plot of the scores for the given classifiers `cl1,cl2`.
getScore(Tensor, int[][]) - Static method in class de.jstacs.algorithms.graphs.DAG
  Returns the score for any graph.
getScore(Sequence, int) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
  This method returns the score for a given sequence and a given class.
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
  This method returns the score for a given sequence and a given class.
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifier.MappingClassifier
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
getScore(Sequence, int, boolean) - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
getScoreForBestRun() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  Returns the value of optimized function from the best run of the last training
getScoreForPath(Tensor, int, byte, int[]) - Static method in class de.jstacs.algorithms.graphs.DAG
  Returns the score for a given path `path` and using the first `l` nodes and dependencies of order `k`.
getScores(Sample) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
  This method returns the scores of the classifier for any sequence in the sample.
getScores(Sample) - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
getScoringFunction(int) - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
  Returns the internally used ScoringFunction with index `i`.
getScoringFunctions() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
  Returns all internally used ScoringFunctions in the internal order.
getScoringFunctions() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  Returns a deep copy of all internal used ScoringFunctions
getSecond() - Method in class de.jstacs.algorithms.Alignment.StringAlignment
  Returns the second string.
getSelected() - Method in class de.jstacs.parameters.CollectionParameter
  Returns the index of the selected value.
getSelected() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
getSensitivityForSpecificity(double[], double[], double) - Static method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions
  This method computes the sensitivity for a given specificity.
getSequence() - Method in class de.jstacs.models.utils.ModelTester.SeqIterator
getShannonEntropy(Model, int) - Static method in class de.jstacs.models.utils.ModelTester
  This method computes the Shannon Entropy for any discrete model `m` and all sequences of `length`, if possible.
getShannonEntropyInBits(Model, int) - Static method in class de.jstacs.models.utils.ModelTester
  This method computes the Shannon Entropy in bits for any discrete model `m` and all sequences of `length`, if possible.
getShortFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
  Returns the `short` which is the value of the `Parameter par`.
getSimplifiedAlphabetContainer(Alphabet[], int[]) - Static method in class de.jstacs.data.AlphabetContainer
  This method creates a new AlphabetContainer that used as less as possible alphabets to describe the container.
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction
  Returns the size of the event space of the random variables that are affected by parameter no.
getSizeOfEventSpaceForRandomVariablesOfParameter(int) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
getStartNode() - Method in class de.jstacs.algorithms.graphs.Edge
getStartParams(boolean, double[]) - Method in class de.jstacs.classifier.scoringFunctionBased.cll.NormConditionalLogLikelihood
  This method enables the user to get the start parameters without creating a new array.
getStartParams(boolean) - Method in class de.jstacs.classifier.scoringFunctionBased.cll.NormConditionalLogLikelihood
getStartParams(boolean) - Method in class de.jstacs.classifier.scoringFunctionBased.OptimizableFunction
  Returns some start parameters.
getStartValue() - Method in class de.jstacs.parameters.RangeParameter
  Returns the start value of a range of parameter values or `null` if no range was specified.
getStationaryDistribution(double[], int) - Static method in class de.jstacs.models.utils.StationaryDistribution
  This method return the stationary distribution.
getStationarySymbolDistribution(double[], int) - Static method in class de.jstacs.models.utils.StationaryDistribution
  This method return the stationary symbol distribution.
getStationarySymbolDistribution() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
getStationarySymbolDistribution() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
getStationarySymbolDistribution() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
getStationarySymbolDistribution() - Method in class de.jstacs.scoringFunctions.VariableLengthScoringFunction
  This method returns the stationary symbol distribution.
getStatistics() - Method in class de.jstacs.results.MeanResultSet
  Returns the means and (if possible the) standard errors of the results in this `MeanResultSet` as a new `NumericalResultSet`.
getStatistics(Sample, double[], int, double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Counts the occurrences of symbols of the `AlphabetContainer` of `s` using `weights`.
getStatisticsOrderTwo(Sample, double[], int, double) - Static method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
  Counts the occurrences of symbols of the `AlphabetContainer` of `s` using `weights`.
getSteps() - Method in class de.jstacs.parameters.RangeParameter
  Returns the number of steps of a range of parameter values or `0` if no range was specified.
getStrandedness() - Method in class de.jstacs.data.sequences.annotation.StrandedLocatedSequenceAnnotationWithLength
  Returns the orientation/strandedness of this annotation.
getString(int) - Method in class de.jstacs.io.StringExtractor
  Returns the string with index `i`.
getStringFromParameter(Parameter) - Static method in class de.jstacs.io.ParameterSetParser
  Returns the `String` which is the value of the `Parameter par`.
getStructure() - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
getStructure() - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel
getStructure() - Method in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
  Returns a string representation of the graph.
getStructure() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
getStructure(Sample, double[], StructureLearner.ModelType, byte, StructureLearner.LearningType) - Method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner
  This method finds the optimal structure (in some sense).
getStructure(Tensor, StructureLearner.ModelType, byte) - Static method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner
  This method can be used to determine the optimal structure.
getStructureFromPath(int[], Tensor) - Static method in class de.jstacs.algorithms.graphs.DAG
  Extracts the structure from a given path and score-"function".
getSubAnnotations() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
  Returns the sub-annotations of this `SequenceAnnotation` as given in the constructor.
getSubContainer(int, int) - Method in class de.jstacs.data.AlphabetContainer
  This method returns a subcontainer for the positions starting at `start` and with length `length`.
getSubSequence(AlphabetContainer, int) - Method in class de.jstacs.data.Sequence
  This method should be used if one wants to create a sample of subsequences of defined length.
getSubSequence(AlphabetContainer, int, int) - Method in class de.jstacs.data.Sequence
  This method should be used if one wants to create a sample of subsequences of defined length.
getSubSequence(int) - Method in class de.jstacs.data.Sequence
  This is an very efficient way to create a subsequence/suffix for sequences with a simple AlphabetContainer.
getSubSequence(int, int) - Method in class de.jstacs.data.Sequence
  This is an very efficient way to create a subsequence of defined length for sequences with a simple AlphabetContainer.
getSuffixSample(int) - Method in class de.jstacs.data.Sample
  This method enables you to use only an suffix of all elements in the current sample.
getSumOfDeviation(Model, Model, int) - Static method in class de.jstacs.models.utils.ModelTester
  This method computes the sum of deviations between the probabilties for the all sequences of `length` for discrete models `m1` and `m2`.
getSumOfDistribution(Model, int) - Static method in class de.jstacs.models.utils.ModelTester
  This method computes the marginal distribution for any discrete model `m` and all sequences of `length`, if possible.
getSumOfHyperparameter() - Method in class de.jstacs.utils.random.DirichletMRGParams
getSumOfHyperparameter() - Method in class de.jstacs.utils.random.ErlangMRGParams
getSumOfWeights() - Method in class de.jstacs.data.Sample.WeightedSampleFactory
  Returns the sum of all weights
getSuperClassOf(T...) - Static method in class de.jstacs.io.ArrayHandler
  This method returns the deepest class in the class hierarchy that is the class or a super class of all instances in the array.
getSymbol(int, double) - Method in class de.jstacs.data.AlphabetContainer
  This method returns a String repsresentation of `val`
getSymbolAt(int) - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
  Returns the symbol at Position `i` in the alphabet
getSymKLDivergence(Model, Model, int) - Static method in class de.jstacs.models.utils.ModelTester
  Returns the difference of the Kullback-Leibler-divergences, i.e.
getTensor(Sample, double[], byte, StructureLearner.LearningType) - Method in class de.jstacs.models.discrete.inhomogeneous.StructureLearner
  This method can be used to compute a tensor that can be used to determine the optimal structure.
getThreshold() - Method in class de.jstacs.classifier.ScoreBasedPerformanceMeasureDefinitions.ThresholdMeasurePair
  This method returns the value of threshold.
getThreshold(double[], int) - Static method in class de.jstacs.classifier.utils.PValueComputation
  This method returns the threshold t that determines if an observed score is significant.
getTopologicalOrder(int[][]) - Static method in class de.jstacs.algorithms.graphs.TopSort
  Returns the topological order of indexes according to `parents2`.
getTopologicalOrder2(byte[][]) - Static method in class de.jstacs.algorithms.graphs.TopSort
  Method to compute a topological ordering for a given graph.
getTrain_TestNumbers(boolean) - Method in class de.jstacs.classifier.assessment.RepeatedSubSamplingAssessParameterSet
getTrueIndexForLastGetBest() - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
  Returns the edge from getBest in an endcoded index.
getType() - Method in class de.jstacs.data.sequences.annotation.SequenceAnnotation
  Returns the type of this `SequenceAnnotation` as given in the constructor
getValidator() - Method in class de.jstacs.parameters.SimpleParameter
  Returns the `ParameterValidator` used in this `SimpleParameter`.
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.AsymmetricTensor
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.SymmetricTensor
getValue(byte, int, int...) - Method in class de.jstacs.algorithms.graphs.tensor.Tensor
  Returns the value for the edge `parents[0],...`
getValue() - Method in class de.jstacs.parameters.CollectionParameter
getValue() - Method in class de.jstacs.parameters.EnumParameter
getValue() - Method in class de.jstacs.parameters.FileParameter
getValue() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
getValue() - Method in class de.jstacs.parameters.Parameter
  Returns the current value of this `Parameter`
getValue() - Method in class de.jstacs.parameters.ParameterSetContainer
getValue() - Method in class de.jstacs.parameters.RangeParameter
getValue() - Method in class de.jstacs.parameters.SimpleParameter
getValue() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Returns the current value of this parameter.
getValueFor(String) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
  Returns the value for the option with key `key`.
getValueFor(int) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
  Returns the value of the option no.
getValueOfAIC(Model, Sample, int) - Static method in class de.jstacs.models.utils.ModelTester
  This method computes the value of Akaikes Information Criterion (AIC).
getValueOfBIC(Model, Sample, int) - Static method in class de.jstacs.models.utils.ModelTester
  This method computes the value of Bayesian Information Criterion (BIC).
getValues() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
  Returns the values of all selected options as an array.
getVersionInformation() - Method in class de.jstacs.utils.REnvironment
getWeight() - Method in class de.jstacs.algorithms.graphs.Edge
getWeight(int) - Method in class de.jstacs.data.Sample.WeightedSampleFactory
  Returns the weight for the sequence with index `index`.
getWeight() - Method in class de.jstacs.utils.ComparableElement
  This method returns the weight of the element.
getWeights() - Method in class de.jstacs.data.Sample.WeightedSampleFactory
  Returns a copy of the weights for the sample.
getWeights() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  This method returns the a deep copy of the weights for each component.
getXMLTag() - Method in class de.jstacs.classifier.AbstractClassifier
  Returns the String that is used as tag for the xml-representation.
getXMLTag() - Method in class de.jstacs.classifier.MappingClassifier
getXMLTag() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
getXMLTag() - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
getXMLTag() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
getXMLTag() - Method in class de.jstacs.models.discrete.Constraint
  Returns the XML-tag that is used for the class to en- or decode.
getXMLTag() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
getXMLTag() - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
getXMLTag() - Method in class de.jstacs.models.discrete.inhomogeneous.FSDAGModel
getXMLTag() - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb
getXMLTag() - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
getXMLTag() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This method returns the XML tag of the instance that is used to build and XML representation
getZ() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Returns the part of the normalization constant of parameters after this parameter in the structure of the network.
GibbsSamplingComponent - Interface in de.jstacs.models.mixture.gibbssampling
  This is the interface that any AbstractModel has to implement if it should be used in a Gibbs Sampling.
goldenRatio(OneDimensionalFunction, double, double, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
  Approximates a minimum (not necessary the global) in the interval [lower,upper].
goldenRatio(OneDimensionalFunction, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
  Approximates a minimum (not necessary the global) in the interval [lower,upper].
GT - Static variable in interface de.jstacs.parameters.validation.Constraint
  The condition is greater than
GUIProgressUpdater - Class in de.jstacs.utils
  This class implements a ProgressUpdater with a GUI.
GUIProgressUpdater(boolean) - Constructor for class de.jstacs.utils.GUIProgressUpdater
  This is the constructor for a GUIProgressUpdaterBar.

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