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 loosing information.

cast(T...) - Static method in class de.jstacs.io.ArrayHandler

This method creates a new array of the super class 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

Creates a new CategoricalResult from its XML-representation.

CategoricalResult(DataType, String, String, Comparable) - Constructor for class de.jstacs.results.CategoricalResult

Creates a result of a primitive categorical datatype 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.

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.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 two alphabets are consistent, i.e. both alphabets use the same symbols.

checkConsistency(AlphabetContainer) - Method in class de.jstacs.data.AlphabetContainer

Checks whether to alphabets are consistent.

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.

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.

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

Re-creates a CisRegulatoryModuleAnnotation from its XML-representation as returned by SequenceAnnotation.toXML().

ClassDimensionException - Exception in de.jstacs.classifier

This class indicates that the classifier should be 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 an instance with default message.

ClassDimensionException(String) - Constructor for exception de.jstacs.classifier.ClassDimensionException

This constructor creates a instance with given message.

Classification - Class in de.jstacs.classifier

This class contains a main-method that allows to compute some performance measures in a very simple way.

Classification() - Constructor for class de.jstacs.classifier.Classification

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 Models, 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 those constructed using the given AbstractModels.

ClassifierAssessmentAssessParameterSet - Class in de.jstacs.classifier.assessment

This class is the super-class used by all ClassifierAssessmentAssessParameterSets.

ClassifierAssessmentAssessParameterSet(Class) - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet

inherited from ParameterSet

ClassifierAssessmentAssessParameterSet() - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet

inherited from ParameterSet

ClassifierAssessmentAssessParameterSet(StringBuffer) - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet

inherited from ParameterSet

ClassifierAssessmentAssessParameterSet(int, boolean) - Constructor for class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet

classify(Sequence) - Method in class de.jstacs.classifier.AbstractClassifier

This method classifies a sequence and returns the index i, with 0 < i < getNumberOfClasses(), of the class to which the sequence is assigned.

classify(Sample) - Method in class de.jstacs.classifier.AbstractClassifier

This method classifies all sequences of a sample and returns the index i, with 0 < i < getNumberOfClasses(), of the class to which the sequence is assigned.

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

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.

CLLClassifier - Class in de.jstacs.classifier.scoringFunctionBased.cll

This class implements the conditional log likelihood classifier.

CLLClassifier(CLLClassifierParameterSet, ScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier

The default constructor.

CLLClassifier(CLLClassifierParameterSet, LogPrior, ScoringFunction...) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier

The default constructor.

CLLClassifier(StringBuffer) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier

This is the constructor for 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

This is the constructor for Storable.

CLLClassifierParameterSet(AlphabetContainer, int, byte, double, double, double, boolean, boolean, boolean) - Constructor for class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifierParameterSet

The default constructor.

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.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

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 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.InstanceParameterSet

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.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.MRFScoringFunction

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 function and enables the user to do some postprocessing.

close() - Method in class de.jstacs.utils.NullProgressUpdater

closes the supervision

close() - Method in class de.jstacs.utils.REnvironment

Close the Renviroment and removes all files from the server.

close() - Method in class de.jstacs.utils.SafeOutputStream

Closes this 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, 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

Restores an instance of CollectionParameter from a string representation

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 InconsistentCollectionExceptionmessage

CombinationIterator - Class in de.jstacs.models.discrete.inhomogeneous

This class can be used for iterating of all possible combinations

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 containing the complementary current sequence.

complement(int, int) - Method in class de.jstacs.data.Sequence

This method returns a new instance of sequence containing a part of the complementary current sequence.

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 for to compute the complement.

ComplementableDiscreteAlphabet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.ComplementableDiscreteAlphabet

The constructor for the Storable interface.

ComplementableDiscreteAlphabet(String[], boolean) - Constructor for class de.jstacs.data.alphabets.ComplementableDiscreteAlphabet

The main constructor.

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.

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

CompositeModel(StringBuffer) - Constructor for class de.jstacs.models.CompositeModel

The constructor for the Storable interface.

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.

computeLogGammaSum() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction

This method is used to precompute 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).

computeMaximalKDAG(Tensor) - Static method in class de.jstacs.algorithms.graphs.DAG

Computes the maximal k-DAG, i.e. the k-DAG that maximize the score given by the tensor.

computeMaxKDAG(SymmetricTensor) - Static method in class de.jstacs.algorithms.graphs.DAG

Computes the maximal k-DAG, i.e. the k-DAG that maximize the score given by the tensor.

ConfusionMatrix - Class in de.jstacs.classifier

This class holds the confusion matrix of a classifier.

ConfusionMatrix(int) - Constructor for class de.jstacs.classifier.ConfusionMatrix

This constructor creates an instance with a given number of classes.

ConfusionMatrix(StringBuffer) - Constructor for class de.jstacs.classifier.ConfusionMatrix

This is the constructor for 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 Ribiere 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 Ribiere.

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 Ribiere called Polak-Ribiere-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 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 constructor for creating an object from an StringBuffer.

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

The class manipulate 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 the addConstraint()-method.

ConstraintValidator(StringBuffer) - Constructor for class de.jstacs.parameters.validation.ConstraintValidator

Creates a new ConstraintValidator from its XML-representation.

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 minimum and a maximum value

ContinuousAlphabet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet

Extracts the alphabet from the StringBuffer.

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 ContinuousAlphabetParameterSet with empty values.

ContinuousAlphabet.ContinuousAlphabetParameterSet(double, double) - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet.ContinuousAlphabetParameterSet

Creates a new ContinuousAlphabetParameterSet from a minimum and a maximum value

ContinuousAlphabet.ContinuousAlphabetParameterSet(StringBuffer) - Constructor for class de.jstacs.data.alphabets.ContinuousAlphabet.ContinuousAlphabetParameterSet

Creates a new ContinousParameterSet from its XML-representation.

continuousVal(int) - Method in class de.jstacs.data.Sequence

Returns the continuous value of position pos.

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 to a target 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 check 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 that can initially be received.

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) constr with the weighted absolute frequency of the sample data and computes the frequencies will not be computed.

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 CLLClassifier by using the cross-product of the given ScoringFunctions.

create(AlphabetContainer, String) - Static method in class de.jstacs.data.Sequence

Creates a sequence 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 from a string based on the given AlphabetContainer using the given delimiter.

create(AlphabetContainer, SequenceAnnotation[], String, String) - Static method in class de.jstacs.data.Sequence

Creates a sequence from a string based on the given AlphabetContainer using the given delimiter.

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.

createMatrix(String, int[][]) - Method in class de.jstacs.utils.REnvironment

Creates a matrix of integers.

createMatrix(String, double[][]) - Method in class de.jstacs.utils.REnvironment

Creates a matrix of doubles.

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.

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 integers.

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.