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

C

canBeCastedFromTo(DataType, DataType) - Static method in enum de.jstacs.DataType
Checks if the DataType from can be casted to the DataType to without losing information.
cast(T...) - Static method in class de.jstacs.io.ArrayHandler
This method creates a new array of the superclass of all elements of the given array and copies the elements.
CategoricalResult - Class in de.jstacs.results
A class for categorical results (i.e. non-numerical results) for primitives and Strings.
CategoricalResult(StringBuffer) - Constructor for class de.jstacs.results.CategoricalResult
The standard constructor for the interface Storable.
CategoricalResult(DataType, String, String, Comparable) - Constructor for class de.jstacs.results.CategoricalResult
Creates a result of a primitive categorical data type or a String .
CategoricalResult(String, String, String) - Constructor for class de.jstacs.results.CategoricalResult
Creates a result of a String.
CategoricalResult(String, String, boolean) - Constructor for class de.jstacs.results.CategoricalResult
Creates a result of a boolean.
CDFOfNormal - Class in de.jstacs.scoringFunctions.mix.motifSearch
This class enables to compute the

The code is a simplified version of pnorm.c from R (version 2.8.0 downloaded at 07.12.2008 about 19:30).
CDFOfNormal() - Constructor for class de.jstacs.scoringFunctions.mix.motifSearch.CDFOfNormal
 
check(Sample) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
This method checks if the given Sample can be used.
check(Sequence) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
This method checks if the given Sequence can be used.
check(Sequence, int, int) - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
Checks some conditions on a Sequence.
check(Sequence, int, int) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel
Checks some constraints, these are in general conditions on the AlphabetContainer of a (sub)Sequence between startpos und endpos.
check(Sequence, int, int) - Method in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
 
check(Object) - Method in interface de.jstacs.parameters.validation.Constraint
Checks value for the constraint defined in the Constraint.
check(Object) - Method in class de.jstacs.parameters.validation.ReferenceConstraint
 
check(Object) - Method in class de.jstacs.parameters.validation.SimpleReferenceConstraint
 
check(Object) - Method in class de.jstacs.parameters.validation.SimpleStaticConstraint
 
checkAcyclic(int, int[][]) - Static method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
This method checks whether a given graph is acyclic.
checkConsistency(Alphabet) - Method in class de.jstacs.data.Alphabet
Checks if this Alphabet is consistent consistent with another Alphabet, i.e. both Alphabets use the same symbols.
checkConsistency(AlphabetContainer) - Method in class de.jstacs.data.AlphabetContainer
Checks if this AlphabetContainer is consistent consistent with another AlphabetContainer.
checkDatatype(DataType, Object) - Static method in class de.jstacs.results.Result
This method provides the possibility to check the compliance of some result value with one of the pre-defined DataTypes before creating a new Result and possibly running into an Exception.
checkLength(int, int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method checks if the length l of the model with index index is capable for the current instance.
checkLength(int, int) - Method in class de.jstacs.models.mixture.motif.HiddenMotifMixture
 
checkModelsForGibbsSampling() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method can be used to check whether the necessary models have implemented the GibbsSamplingComponent.
checkValue(Object) - Method in class de.jstacs.parameters.CollectionParameter
Returns true if the key specified by value is in the set of keys of this CollectionParameter.
checkValue(Object) - Method in class de.jstacs.parameters.FileParameter
 
checkValue(Object) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
checkValue(Object) - Method in class de.jstacs.parameters.Parameter
Checks the value for correctness, e.g. for numerical parameters this might be checking if the value is within specified bounds.
checkValue(Object) - Method in class de.jstacs.parameters.ParameterSetContainer
 
checkValue(Object) - Method in class de.jstacs.parameters.RangeParameter
 
checkValue(Object) - Method in class de.jstacs.parameters.SimpleParameter
 
checkValue(Object) - Method in class de.jstacs.parameters.validation.ConstraintValidator
 
checkValue(Object) - Method in class de.jstacs.parameters.validation.NumberValidator
 
checkValue(Object) - Method in interface de.jstacs.parameters.validation.ParameterValidator
Returns true if the value is valid and false otherwise.
checkValue(Object) - Method in class de.jstacs.parameters.validation.StorableValidator
Checks the value of value.
chooseFromDistr(Constraint, int, int, double) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel
Chooses a value in [0,end-start] according to the distribution encoded in the frequencies of distr between the indices start and end.
Chu_Liu_Edmonds - Class in de.jstacs.algorithms.graphs
This class implements the algorithm of Chu_Liu_Edmonds to determine an optimal branching (optimal directed graph of order 1).
CisRegulatoryModuleAnnotation - Class in de.jstacs.data.sequences.annotation
Annotation for a cis-regulatory module as defined by a set of MotifAnnotations of the motifs in the module.
CisRegulatoryModuleAnnotation(String, MotifAnnotation[], Result...) - Constructor for class de.jstacs.data.sequences.annotation.CisRegulatoryModuleAnnotation
Creates a new CisRegulatoryModuleAnnotation from a set of motifs and possibly additional annotations.
CisRegulatoryModuleAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.CisRegulatoryModuleAnnotation
The standard constructor for the interface Storable.
cl - Variable in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction
The number of different classes.
ClassDimensionException - Exception in de.jstacs.classifier
This class indicates that a classifier is defined for less than 2 classes or is defined over a different number of classes than given (e.g. by an array of Samples).
ClassDimensionException() - Constructor for exception de.jstacs.classifier.ClassDimensionException
This constructor creates a ClassDimensionException with the default error message ("The number of classes in the classfier differs from the given number.
ClassDimensionException(String) - Constructor for exception de.jstacs.classifier.ClassDimensionException
This constructor creates a ClassDimensionException with given error message.
ClassificationVisualizer - Class in de.jstacs.classifier.utils
This class enables you to visualize some classifier results.
ClassifierAssessment - Class in de.jstacs.classifier.assessment
Class defining an assessment of classifiers.
ClassifierAssessment(AbstractClassifier[], Model[][], boolean, boolean) - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessment
Creates a new ClassifierAssessment from an array of AbstractClassifiers and a two-dimensional array of Model s, which are combined to additional classifiers.
ClassifierAssessment(AbstractClassifier...) - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessment
Creates a new ClassifierAssessment from a set of AbstractClassifiers.
ClassifierAssessment(boolean, Model[]...) - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessment
Creates a new ClassifierAssessment from a set of Models.
ClassifierAssessment(AbstractClassifier[], boolean, Model[]...) - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessment
This constructor allows to assess a collection of given AbstractClassifiers and, in addition, classifiers that will be constructed using the given AbstractModels.
ClassifierAssessmentAssessParameterSet - Class in de.jstacs.classifier.assessment
This class is the superclass used by all ClassifierAssessmentAssessParameterSets.
ClassifierAssessmentAssessParameterSet() - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
Constructs a new ClassifierAssessmentAssessParameterSet with empty parameter values.
ClassifierAssessmentAssessParameterSet(StringBuffer) - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
The standard constructor for the interface Storable.
ClassifierAssessmentAssessParameterSet(int, boolean) - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
Constructs a new ClassifierAssessmentAssessParameterSet with given parameter values.
classify(Sequence) - Method in class de.jstacs.classifier.AbstractClassifier
This method classifies a sequence and returns the index i of the class to which the sequence is assigned with 0 < i < getNumberOfClasses().
classify(Sample) - Method in class de.jstacs.classifier.AbstractClassifier
This method classifies all sequences of a sample and returns an array of indices of the classes to which the respective sequences are assigned with for each index i in the array 0 < i < getNumberOfClasses().
classify(Sequence) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
 
classify(Sequence, boolean) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
This method classifies a Sequence.
classify(Sample) - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
 
classMus - Variable in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior
The means for the class parameters, as specified by the user.
classVars - Variable in class de.jstacs.classifier.scoringFunctionBased.logPrior.SeparateLogPrior
The variances for the class parameters, as specified by the user.
clazz - Variable in class de.jstacs.classifier.scoringFunctionBased.AbstractOptimizableFunction
The class parameters.
clear() - Method in interface de.jstacs.motifDiscovery.history.History
This method clears the history, i.e. it removes all operations from the history.
clear() - Method in class de.jstacs.motifDiscovery.history.RestrictedRepeatHistory
 
clear() - Method in class de.jstacs.utils.DoubleList
Removes all elements from the list.
clear() - Method in class de.jstacs.utils.IntList
Removes all elements from the list.
clearHistoryArray(History[][]) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
This method clears all elements of an History-array, so that it can be used again.
CLLClassifier - Class in de.jstacs.classifier.scoringFunctionBased.cll
This class implements the conditional log likelihood (CLL) classifier.
CLLClassifier(CLLClassifierParameterSet, ScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
The default constructor that creates a new CLLClassifier from a given parameter set and ScoringFunctions for the classes.
CLLClassifier(CLLClassifierParameterSet, LogPrior, ScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
The default constructor that creates a new CLLClassifier from a given parameter set, a prior and ScoringFunctions for the classes.
CLLClassifier(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
The standard constructor for the interface Storable.
CLLClassifierParameterSet - Class in de.jstacs.classifier.scoringFunctionBased.cll
This class contains the parameters for the CLLClassifier.
CLLClassifierParameterSet(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifierParameterSet
The standard constructor for the interface Storable.
CLLClassifierParameterSet(AlphabetContainer, int, byte, double, double, double, boolean, OptimizableFunction.KindOfParameter, boolean) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifierParameterSet
The default constructor that constructs a new CLLClassifierParameterSet.
CLLClassifierParameterSet(Class<? extends ScoreClassifier>, AlphabetContainer, int, byte, double, double, double, boolean, OptimizableFunction.KindOfParameter, boolean) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifierParameterSet
The default constructor that constructs a new CLLClassifierParameterSet.
clone() - Method in class de.jstacs.algorithms.graphs.Edge
 
clone() - Method in class de.jstacs.classifier.AbstractClassifier
 
clone() - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
 
clone() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
 
clone() - Method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
 
clone() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
 
clone() - Method in class de.jstacs.data.Alphabet.AlphabetParameterSet
 
clone() - Method in class de.jstacs.data.AlphabetContainerParameterSet.AlphabetArrayParameterSet
 
clone() - Method in class de.jstacs.data.AlphabetContainerParameterSet
 
clone() - Method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
 
clone(T...) - Static method in class de.jstacs.io.ArrayHandler
This method returns a deep copy of an array, i.e. for each element of the array the clone method will be invoked.
clone() - Method in class de.jstacs.models.AbstractModel
Follows the conventions of Object's clone()-method.
clone() - Method in class de.jstacs.models.CompositeModel
 
clone() - Method in class de.jstacs.models.discrete.Constraint
 
clone() - Method in class de.jstacs.models.discrete.DGMParameterSet
 
clone() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
 
clone() - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousMM
 
clone() - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
 
clone() - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
 
clone() - Method in class de.jstacs.models.discrete.inhomogeneous.InhCondProb
 
clone() - Method in class de.jstacs.models.discrete.inhomogeneous.InhConstraint
 
clone() - Method in class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
 
clone() - Method in class de.jstacs.models.discrete.inhomogeneous.MEMConstraint
 
clone() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureClassifier
 
clone() - Method in class de.jstacs.models.discrete.inhomogeneous.shared.SharedStructureMixture
 
clone() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
 
clone() - Method in class de.jstacs.models.mixture.gibbssampling.BurnInTest
 
clone() - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
In this method the reader is set to null and the paramsFile is cloned.
clone() - Method in class de.jstacs.models.mixture.motif.HiddenMotifMixture
 
clone() - Method in class de.jstacs.models.mixture.motif.positionprior.PositionPrior
 
clone() - Method in interface de.jstacs.models.Model
Creates a clone (deep copy) of the current Model instance.
clone() - Method in class de.jstacs.models.UniformModel
 
clone() - Method in interface de.jstacs.motifDiscovery.history.History
This method returns a deep copy of the instance
clone() - Method in class de.jstacs.motifDiscovery.history.RestrictedRepeatHistory
 
clone() - Method in class de.jstacs.parameters.CollectionParameter
 
clone() - Method in class de.jstacs.parameters.ExpandableParameterSet
 
clone() - Method in class de.jstacs.parameters.FileParameter
 
clone() - Method in class de.jstacs.parameters.FileParameter.FileRepresentation
 
clone() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
clone() - Method in class de.jstacs.parameters.Parameter
 
clone() - Method in class de.jstacs.parameters.ParameterSet
Creates a full clone (deep copy) of this ParameterSet.
clone() - Method in class de.jstacs.parameters.ParameterSetContainer
 
clone() - Method in class de.jstacs.parameters.RangeParameter
 
clone() - Method in class de.jstacs.parameters.SequenceScoringParameterSet
 
clone() - Method in class de.jstacs.parameters.SimpleParameter
 
clone() - Method in class de.jstacs.parameters.SimpleParameterSet
 
clone() - Method in interface de.jstacs.parameters.validation.Constraint
This method returns a deep copy of the current instance.
clone() - Method in class de.jstacs.parameters.validation.ConstraintValidator
 
clone() - Method in class de.jstacs.parameters.validation.NumberValidator
 
clone() - Method in interface de.jstacs.parameters.validation.ParameterValidator
This method returns a deep copy of the current instance.
clone() - Method in class de.jstacs.parameters.validation.ReferenceConstraint
 
clone() - Method in class de.jstacs.parameters.validation.SimpleReferenceConstraint
 
clone() - Method in class de.jstacs.parameters.validation.SimpleStaticConstraint
 
clone() - Method in class de.jstacs.parameters.validation.StorableValidator
 
clone() - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
 
clone() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
 
clone() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
 
clone() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
 
clone() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTExplainingAwayResidual
 
clone() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures.BTMutualInformation
 
clone() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
 
clone() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
 
clone() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
 
clone() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
 
clone() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
 
clone() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
 
clone() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
 
clone() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
 
clone() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture
 
clone() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.PositionScoringFunction
 
clone() - Method in class de.jstacs.scoringFunctions.mix.motifSearch.SkewNormalLikeScoringFunction
 
clone() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
 
clone() - Method in class de.jstacs.scoringFunctions.NormalizedScoringFunction
 
clone() - Method in interface de.jstacs.scoringFunctions.ScoringFunction
Creates a clone (deep copy) of the current ScoringFunction instance.
cloneFunctions(NormalizableScoringFunction[]) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method clones the given array of functions and enables the user to do some post-processing.
cloneHomProb(HomogeneousModel.HomCondProb[]) - Method in class de.jstacs.models.discrete.homogeneous.HomogeneousModel
Clones the given array of conditional probabilities.
close() - Method in class de.jstacs.utils.NullProgressUpdater
Closes the supervision.
close() - Method in class de.jstacs.utils.REnvironment
Closes the REnvironment and removes all files from the server.
close() - Method in class de.jstacs.utils.SafeOutputStream
Closes the SafeOutputStream by closing the OutputStream this stream was constructed of.
CollectionParameter - Class in de.jstacs.parameters
Class for a collection parameter, i.e. a parameter that provides some collection of possible values the user can choose from.
CollectionParameter(ParameterSet, int, int, boolean, String, String, boolean, DataType, String, boolean) - Constructor for class de.jstacs.parameters.CollectionParameter
Creates a new CollectionParameter from the necessary field.
CollectionParameter(DataType, String[], Object[], String, String, boolean) - Constructor for class de.jstacs.parameters.CollectionParameter
Constructor for a CollectionParameter.
CollectionParameter(DataType, String[], Object[], String[], String, String, boolean) - Constructor for class de.jstacs.parameters.CollectionParameter
Constructor for a CollectionParameter.
CollectionParameter(ParameterSet[], String[], String[], String, String, boolean) - Constructor for class de.jstacs.parameters.CollectionParameter
Constructor for a CollectionParameter from an array of ParameterSets.
CollectionParameter(InstanceParameterSet[], String, String, boolean) - Constructor for class de.jstacs.parameters.CollectionParameter
Constructor for a CollectionParameter from an array of ParameterSets.
CollectionParameter(StringBuffer) - Constructor for class de.jstacs.parameters.CollectionParameter
The standard constructor for the interface Storable.
CollectionParameter.InconsistentCollectionException - Exception in de.jstacs.parameters
This exception is thrown if the CollectionParameter is inconsistent for some reason.
CollectionParameter.InconsistentCollectionException(String) - Constructor for exception de.jstacs.parameters.CollectionParameter.InconsistentCollectionException
Constructs a new CollectionParameter.InconsistentCollectionException with message message.
CombinationIterator - Class in de.jstacs.models.discrete.inhomogeneous
This class can be used for iterating over all possible combinations (in the sense of combinatorics).
CombinationIterator(int, int) - Constructor for class de.jstacs.models.discrete.inhomogeneous.CombinationIterator
Creates a new CombinationIterator with n elements and at most max selected elements.
comment - Variable in class de.jstacs.parameters.SimpleParameter
A comment on the parameter
comment - Variable in class de.jstacs.results.Result
The comment for the result.
commentTemplate - Variable in class de.jstacs.parameters.ExpandableParameterSet
A template for the comment of the enclosing ParameterSetContainer
ComparableElement<E,C extends Comparable> - Class in de.jstacs.utils
This class is a container for any objects that have to be compared.
ComparableElement(E, C) - Constructor for class de.jstacs.utils.ComparableElement
Creates a new ComparableElement.
compareTo(Edge) - Method in class de.jstacs.algorithms.graphs.Edge
 
compareTo(AlphabetContainer) - Method in class de.jstacs.data.AlphabetContainer
 
compareTo(Alphabet) - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
 
compareTo(Alphabet) - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
 
compareTo(Sequence) - Method in class de.jstacs.data.Sequence
 
compareTo(SimpleResult) - Method in class de.jstacs.results.SimpleResult
 
compareTo(ComparableElement<E, C>) - Method in class de.jstacs.utils.ComparableElement
 
complement() - Method in class de.jstacs.data.Sequence
This method returns a new instance of Sequence.CompositeSequence containing the complementary current Sequence.CompositeSequence.
complement(int, int) - Method in class de.jstacs.data.Sequence
This method returns a new instance of Sequence.CompositeSequence containing a part of the complementary current Sequence.CompositeSequence.
complement(int, int) - Method in class de.jstacs.data.sequences.SparseSequence
 
ComplementableDiscreteAlphabet - Class in de.jstacs.data.alphabets
This abstract class indicates that an alphabet can be used to compute the complement.
ComplementableDiscreteAlphabet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.ComplementableDiscreteAlphabet
The standard constructor for the interface Storable.
ComplementableDiscreteAlphabet(boolean, String...) - Constructor for class de.jstacs.data.alphabets.ComplementableDiscreteAlphabet
Creates a new ComplementableDiscreteAlphabet from a given array of symbols.
componentHyperParams - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The hyperparameters for estimating the probabilities of the components.
componentScore - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This array is used while computing the score.
CompositeLogPrior - Class in de.jstacs.classifier.scoringFunctionBased.logPrior
This class implements a composite prior that can be used for NormalizableScoringFunction.
CompositeLogPrior() - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.CompositeLogPrior
The main constructor.
CompositeLogPrior(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.logPrior.CompositeLogPrior
The constructor for the Storable interface.
CompositeModel - Class in de.jstacs.models
This class is for modelling sequences by modelling the different positions of the each sequence by different models.
CompositeModel(AlphabetContainer, int[], Model...) - Constructor for class de.jstacs.models.CompositeModel
Creates a new CompositeModel.
CompositeModel(StringBuffer) - Constructor for class de.jstacs.models.CompositeModel
The standard constructor for the interface Storable.
compProb - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
This array is used while training to avoid creating many new objects.
computeFreqs(double, Constraint...) - Static method in class de.jstacs.models.discrete.ConstraintManager
This method computes the (smoothed) relative frequencies.
computeGammaNorm() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Computes the Gamma-normalization for the prior.
computeHiddenParameter(double[]) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method has to be invoked during an initialization.
computeLengthOfBurnIn() - Method in class de.jstacs.models.mixture.gibbssampling.AbstractBurnInTest
Computes and returns the length of the burn-in phase using the values from BurnInTest.setValue(double).
computeLengthOfBurnIn() - Method in class de.jstacs.models.mixture.gibbssampling.VarianceRatioBurnInTest
Computes and returns the length of the burn-in phase given by the Variance-Ratio burn-in test.
computeLogGammaSum() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method is used to pre-compute the sum of the logarithm of the gamma functions that is used in the prior.
computeMaximalHP(Tensor) - Static method in class de.jstacs.algorithms.graphs.DAG
The method computes the HP(k) (see DAG).
computeMaximalKDAG(Tensor) - Static method in class de.jstacs.algorithms.graphs.DAG
Computes the maximal k-DAG (see DAG), i.e. the k-DAG that maximizes the score given by a Tensor.
computeMaxKDAG(SymmetricTensor) - Static method in class de.jstacs.algorithms.graphs.DAG
Computes the maximal k-DAG (see DAG), i.e. the k-DAG that maximizes the score given by a SymmetricTensor.
ConfusionMatrix - Class in de.jstacs.classifier
This class holds the confusion matrix of a classifier.
ConfusionMatrix(int) - Constructor for class de.jstacs.classifier.ConfusionMatrix
Creates a new ConfusionMatrix with a given number of classes.
ConfusionMatrix(StringBuffer) - Constructor for class de.jstacs.classifier.ConfusionMatrix
The standard constructor for the interface Storable.
CONJUGATE_GRADIENTS_FR - Static variable in class de.jstacs.algorithms.optimization.Optimizer
This constant can be used to specify that conjugate gradients (by Fletcher and Reeves) should be used in the optimize-method.
CONJUGATE_GRADIENTS_PRP - Static variable in class de.jstacs.algorithms.optimization.Optimizer
This constant can be used to specify that conjugate gradients (by Polak and Ribière should be used in the optimize-method.
conjugateGradientsFR(DifferentiableFunction, double[], Optimizer.TerminationCondition, double, double, StartDistanceForecaster, SafeOutputStream, Time) - Static method in class de.jstacs.algorithms.optimization.Optimizer
The conjugate gradient algorithm by Fletcher and Reeves.
conjugateGradientsPR(DifferentiableFunction, double[], Optimizer.TerminationCondition, double, double, StartDistanceForecaster, SafeOutputStream, Time) - Static method in class de.jstacs.algorithms.optimization.Optimizer
The conjugate gradient algorithm by Polak and Ribière.
conjugateGradientsPRP(DifferentiableFunction, double[], Optimizer.TerminationCondition, double, double, StartDistanceForecaster, SafeOutputStream, Time) - Static method in class de.jstacs.algorithms.optimization.Optimizer
The conjugate gradient algorithm by Polak and Ribière called "Polak-Ribière-Positive".
ConstantStartDistance - Class in de.jstacs.algorithms.optimization
The most simple StartDistanceForecaster that returns always the same value.
ConstantStartDistance(double) - Constructor for class de.jstacs.algorithms.optimization.ConstantStartDistance
This constructor creates an instance of ConstantStartDistance that returns always the given value.
Constraint - Class in de.jstacs.models.discrete
The main class for all constraints on models.
Constraint(int[], int) - Constructor for class de.jstacs.models.discrete.Constraint
The main constructor.
Constraint(StringBuffer) - Constructor for class de.jstacs.models.discrete.Constraint
The standard constructor for the interface Storable.
Constraint - Interface in de.jstacs.parameters.validation
Interface for a constraint that must be fulfilled in a ConstraintValidator.
ConstraintManager - Class in de.jstacs.models.discrete
This class manipulates and manages some constraints.
constraintParameter - Variable in class de.jstacs.parameters.validation.ReferenceConstraint
The reference to the Parameter that is part of the condition.
constraints - Variable in class de.jstacs.models.discrete.inhomogeneous.DAGModel
The constraints for the model.
ConstraintValidator - Class in de.jstacs.parameters.validation
Class for a ParameterValidator that is based on Constraints.
ConstraintValidator() - Constructor for class de.jstacs.parameters.validation.ConstraintValidator
Creates a new ConstraintValidator having an empty list of Constraints, i.e. the constraints of this ConstraintValidator are always fulfilled before additional Constraints are added using ConstraintValidator.addConstraint(Constraint).
ConstraintValidator(StringBuffer) - Constructor for class de.jstacs.parameters.validation.ConstraintValidator
The standard constructor for the interface Storable.
CONTAINS_ALWAYS_A_MOTIF - Static variable in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture
This constant indicates that in each sequence has one binding site of a motif instance (similar to OOPS).
CONTAINS_SOMETIMES_A_MOTIF - Static variable in class de.jstacs.scoringFunctions.mix.motifSearch.HiddenMotifsMixture
This constant indicates that a sequence possibly has one binding site of a motif instance (similar to ZOOPS).
content - Variable in class de.jstacs.data.sequences.RecursiveSequence
The internal sequence.
context - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
The context of this parameter.
continueIterations(double[], double[][]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method will run the train algorithm for the current model on the internal sample.
continueIterations(double[], double[][], int, int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method will run the train algorithm for the current model on the internal sample.
ContinuousAlphabet - Class in de.jstacs.data.alphabets
Class for a continuous alphabet.
ContinuousAlphabet(ContinuousAlphabet.ContinuousAlphabetParameterSet) - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet
The constructor for the InstantiableFromParameterSet interface.
ContinuousAlphabet(double, double) - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet
Creates a new ContinuousAlphabet from a minimal and a maximal value.
ContinuousAlphabet() - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet
Creates a new ContinuousAlphabet with minimum and maximum value being -Double.MAX_VALUE and Double.MAX_VALUE, respectively.
ContinuousAlphabet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet
The standard constructor for the interface Storable.
ContinuousAlphabet.ContinuousAlphabetParameterSet - Class in de.jstacs.data.alphabets
Class for the ParameterSet of a ContinuousAlphabet.
ContinuousAlphabet.ContinuousAlphabetParameterSet() - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet.ContinuousAlphabetParameterSet
Creates a new ContinuousAlphabet.ContinuousAlphabetParameterSet with empty values.
ContinuousAlphabet.ContinuousAlphabetParameterSet(double, double) - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet.ContinuousAlphabetParameterSet
Creates a new ContinuousAlphabet.ContinuousAlphabetParameterSet from a minimum and a maximum value.
ContinuousAlphabet.ContinuousAlphabetParameterSet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet.ContinuousAlphabetParameterSet
The standard constructor for the interface Storable .
continuousVal(int) - Method in class de.jstacs.data.Sequence
Returns the continuous value at position pos of the Sequence.CompositeSequence.
continuousVal(int) - Method in class de.jstacs.data.sequences.ArbitrarySequence
 
continuousVal(int) - Method in class de.jstacs.data.sequences.DiscreteSequence
 
continuousVal(int) - Method in class de.jstacs.data.sequences.RecursiveSequence
 
copy(String, String) - Static method in class de.jstacs.io.FileManager
This method copies a File in a faster manner.
copy(String, String, byte[]) - Static method in class de.jstacs.io.FileManager
This method copies a File in a faster manner using a specified buffer.
copy(ParameterTree) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Copies the values of the parameters from another ParameterTree.
copyDiff(File, File, Date, boolean, FileFilter) - Static method in class de.jstacs.io.FileManager
This method copies all Files and directories, if selected, from a source File, i.e. directory, to a target File, i.e. directory, that have been modified after a predefined date.
copyFileFromServer(String, String, boolean) - Method in class de.jstacs.utils.REnvironment
Copies a file from the server to the local machine.
copyFileFromServer(String, String, RConnection) - Static method in class de.jstacs.utils.RUtils
This method copies a file from the server to the client.
copyFileToServer(String, String, boolean) - Method in class de.jstacs.utils.REnvironment
Copies a file from the local machine to the server.
copyFileToServer(File, String, RConnection) - Static method in class de.jstacs.utils.RUtils
Copies a file to the R side.
copyFileToServer(String, String, RConnection) - Static method in class de.jstacs.utils.RUtils
Copies a file to the R side.
count(int[][], byte) - Method in class de.jstacs.models.discrete.inhomogeneous.BayesianNetworkModel
Counts the occurrence of the different indegrees and checks if the conventions are met.
count - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
The counts for this parameter.
countElements() - Method in class de.jstacs.io.SymbolExtractor
Counts the number of elements (symbols) that can be received initially.
counter - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The current index of the parameter set while adjustment (optimization).
counter - Variable in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
The counter for the sampling steps of each sampling.
countInhomogeneous(AlphabetContainer, int, Sample, double[], boolean, Constraint...) - Static method in class de.jstacs.models.discrete.ConstraintManager
Fills the (inhomogeneous) Constraint constr with the weighted absolute frequencies of the Sample data.
counts - Variable in class de.jstacs.models.discrete.Constraint
The counts for each specific constraint.
create(CLLClassifierParameterSet, LogPrior, ScoringFunction[]...) - Static method in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
This method creates an array of CLLClassifiers by using the cross-product of the given ScoringFunctions.
create(AlphabetContainer, String) - Static method in class de.jstacs.data.Sequence
Creates a Sequence.CompositeSequence from a String based on the given AlphabetContainer using the standard delimiter for this AlphabetContainer.
create(AlphabetContainer, String, String) - Static method in class de.jstacs.data.Sequence
Creates a Sequence.CompositeSequence from a String based on the given AlphabetContainer using the given delimiter delim.
create(AlphabetContainer, SequenceAnnotation[], String, String) - Static method in class de.jstacs.data.Sequence
Creates a Sequence.CompositeSequence from a String based on the given AlphabetContainer using the given delimiter delim and some annotation for the Sequence.CompositeSequence.
createConstraints(AbstractList<int[]>, int[], int[]) - Static method in class de.jstacs.models.discrete.ConstraintManager
Creates the constraints for a part of a model.
createConstraints(AbstractList<int[]>, int[]) - Static method in class de.jstacs.models.discrete.ConstraintManager
Creates the constraints of a model.
createConstraints(int[][]) - Method in class de.jstacs.models.discrete.inhomogeneous.DAGModel
This method creates the constraints for a given structure.
createDefaultClassWeights(int, double) - Method in class de.jstacs.classifier.AbstractScoreBasedClassifier
This method creates new class weights.
createHistoryArray(ScoringFunction[], History) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
This method creates a History-array that can be used in an optimization.
createMatrix(String, int[][]) - Method in class de.jstacs.utils.REnvironment
Creates a matrix of ints.
createMatrix(String, double[][]) - Method in class de.jstacs.utils.REnvironment
Creates a matrix of doubles.
createMinimalNewLengthArray(ScoringFunction[]) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
This method creates a minimalNewLength-array that can be used in an optimization.
createParameterSet(Object[], String[], String[]) - Method in class de.jstacs.parameters.CollectionParameter
Creates a new ParameterSet from an array of values, an array of names and an array of comments.
createResult(String, String, DataType, Object) - Static method in class de.jstacs.results.Result
Factory method to create a new Result.
createSeqWeightsArray() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
Creates an array that can be used for weighting sequences in the algorithm.
createSeqWeightsArray() - Method in class de.jstacs.models.mixture.motif.SingleHiddenMotifMixture
 
createStructure(Sample[], double[][]) - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
Creates the structure that will be used in the optimization.
createTrees(Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
Creates the tree structures that represent the context (array BayesianNetworkScoringFunction.trees) and the parameter objects BayesianNetworkScoringFunction.parameters using the given Measure BayesianNetworkScoringFunction.structureMeasure.
createVector(String, String[]) - Method in class de.jstacs.utils.REnvironment
Creates a vector of Strings.
createVector(String, int[]) - Method in class de.jstacs.utils.REnvironment
Creates a vector of ints.
createVector(String, long[]) - Method in class de.jstacs.utils.REnvironment
Creates a vector of longs.
createVector(String, double[]) - Method in class de.jstacs.utils.REnvironment
Creates a vector of doubles.

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