A B C D E F G H I K L M N O P Q R S T U V W X

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 Sequences 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 Results 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.

A B C D E F G H I K L M N O P Q R S T U V W X