Uses of Interface
de.jstacs.Storable

Packages that use Storable
de.jstacs.classifier This package provides the framework for any classifier. 
de.jstacs.classifier.assessment This package allows to assess classifiers. 
de.jstacs.classifier.modelBased Provides the classes for Classifiers that are based on Model
de.jstacs.classifier.scoringFunctionBased Provides the classes for Classifiers that are based on ScoringFunctions. 
de.jstacs.classifier.scoringFunctionBased.cll Provides the implementation of the log conditional likelihood as an OptimizableFunction and a classifier that uses log conditional likelihood or supervised posterior to learn the parameters of a set of ScoringFunctions 
de.jstacs.classifier.scoringFunctionBased.logPrior Provides a general definition of a parameter log-prior and a number of implementations of Laplace and Gaussian priors 
de.jstacs.data Provides classes for the representation of data. 
de.jstacs.data.alphabets Provides classes for the representation of discrete and continuous alphabets, including a DNAAlphabet for the most common case of DNA-sequences 
de.jstacs.data.sequences.annotation Provides the facilities to annotate Sequences using a number of pre-defined annotation types, or additional implementations of the SequenceAnnotation class 
de.jstacs.io Provides classes for reading data from and writing to a file and storing a number of datatypes, including all primitives, arrays of primitives, and Storables to an XML-representation 
de.jstacs.models Provides the interface Model and its abstract implementation AbstractModel, which is the super class of all other models. 
de.jstacs.models.discrete   
de.jstacs.models.discrete.homogeneous   
de.jstacs.models.discrete.homogeneous.parameters   
de.jstacs.models.discrete.inhomogeneous This package contains various inhomogeneous models. 
de.jstacs.models.discrete.inhomogeneous.parameters   
de.jstacs.models.discrete.inhomogeneous.shared   
de.jstacs.models.mixture This package is the super package for any mixture model. 
de.jstacs.models.mixture.gibbssampling This package contains many classes that can be used while a Gibbs sampling. 
de.jstacs.models.mixture.motif   
de.jstacs.models.mixture.motif.positionprior   
de.jstacs.motifDiscovery This package provides the framework including the interface for any de novo motif discoverer 
de.jstacs.parameters This package provides classes for parameters that establish a general convention for the description of parameters as defined in the Parameter-interface. 
de.jstacs.parameters.validation Provides classes for the validation of Parameter values 
de.jstacs.results This package provides classes for results and sets of results. 
de.jstacs.scoringFunctions Provides ScoringFunctions that can be used in a ScoreClassifier
de.jstacs.scoringFunctions.directedGraphicalModels Provides ScoringFunctions that are equivalent to directed graphical models. 
de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures Provides the facilities to learn the structure of a BayesianNetworkScoringFunction
de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures Provides the facilities to learn the structure of a BayesianNetworkScoringFunction as a Bayesian tree using a number of measures to define a rating of structures 
de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures Provides the facilities to learn the structure of a BayesianNetworkScoringFunction as a permuted Markov model using a number of measures to define a rating of structures 
de.jstacs.scoringFunctions.homogeneous Provides ScoringFunctions that are homogeneous, i.e. model probabilities or scores independent of the position within a sequence 
de.jstacs.scoringFunctions.mix Provides ScoringFunctions that are mixtures of other ScoringFunctions. 
de.jstacs.scoringFunctions.mix.motifSearch   
de.jstacs.utils This package contains a bundle of useful classes and interfaces like ... 
 

Uses of Storable in de.jstacs.classifier
 

Classes in de.jstacs.classifier that implement Storable
 class AbstractClassifier
          The super class for any classifier.
 class AbstractScoreBasedClassifier
          This class is the main class for all score based classifiers.
static class AbstractScoreBasedClassifier.DoubleTableResult
          This class is for Results given as a table of double s.
 class ConfusionMatrix
          This class holds the confusion matrix of a classifier.
 class MappingClassifier
          This class allows the user to train the classifier on a given number of classes and to evaluate the classifier on a smaller number of classes by mapping classes together.
 class MeasureParameters
          This class holds the parameters for the evaluate-methods of a classifier.
 

Uses of Storable in de.jstacs.classifier.assessment
 

Classes in de.jstacs.classifier.assessment that implement Storable
 class ClassifierAssessmentAssessParameterSet
          This class is the superclass used by all ClassifierAssessmentAssessParameterSets.
 class KFoldCVAssessParameterSet
          This class implements a ClassifierAssessmentAssessParameterSet that must be used to call method assess( ... ) of a KFoldCrossValidation.
 class RepeatedHoldOutAssessParameterSet
          This class implements a ClassifierAssessmentAssessParameterSet that must be used to call method assess( ... ) of a RepeatedHoldOutExperiment.
 class RepeatedSubSamplingAssessParameterSet
          This class implements a ClassifierAssessmentAssessParameterSet that must be used to call method assess( ... ) of a RepeatedSubSamplingExperiment.
 class Sampled_RepeatedHoldOutAssessParameterSet
          This class implements a ClassifierAssessmentAssessParameterSet that must be used to call the method assess( ... ) of a Sampled_RepeatedHoldOutExperiment.
 

Uses of Storable in de.jstacs.classifier.modelBased
 

Classes in de.jstacs.classifier.modelBased that implement Storable
 class ModelBasedClassifier
          This class is the main class for all model based classifiers.
 

Uses of Storable in de.jstacs.classifier.scoringFunctionBased
 

Classes in de.jstacs.classifier.scoringFunctionBased that implement Storable
 class ScoreClassifier
          This abstract class implements the main functionality of a ScoringFunction based classifier.
 class ScoreClassifierParameterSet
          A set of Parameters for any ScoreClassifier.
 

Uses of Storable in de.jstacs.classifier.scoringFunctionBased.cll
 

Classes in de.jstacs.classifier.scoringFunctionBased.cll that implement Storable
 class CLLClassifier
          This class implements the conditional log likelihood (CLL) classifier.
 class CLLClassifierParameterSet
          This class contains the parameters for the CLLClassifier.
 

Uses of Storable in de.jstacs.classifier.scoringFunctionBased.logPrior
 

Classes in de.jstacs.classifier.scoringFunctionBased.logPrior that implement Storable
 class CompositeLogPrior
          This class implements a composite prior that can be used for NormalizableScoringFunction.
 class DoesNothingLogPrior
          This class defines a LogPrior that does not penalize any parameter.
 class LogPrior
          The abstract class for any log-prior used e.g. for maximum supervised posterior optimization.
 class SeparateGaussianLogPrior
          Class for a LogPrior that defines a Gaussian prior on the parameters of a set of NormalizableScoringFunctions and a set of class parameters.
 class SeparateLaplaceLogPrior
          Class for a LogPrior that defines a Laplace prior on the parameters of a set of NormalizableScoringFunctions and a set of class parameters.
 class SeparateLogPrior
          Abstract class for priors that penalize each parameter value independently and have some variances (and possible means) as hyperparameters.
 class SimpleGaussianSumLogPrior
          This class implements a prior that is a product of Gaussian distributions with mean 0 and equal variance for each parameter.
 

Uses of Storable in de.jstacs.data
 

Classes in de.jstacs.data that implement Storable
 class Alphabet
          Class for a set of symbols, i.e. an Alphabet.
static class Alphabet.AlphabetParameterSet
          The super class for the InstanceParameterSet of any Alphabet.
 class AlphabetContainer
          The container for Alphabets used in a Sequence, Sample, AbstractModel or ... .
 class AlphabetContainerParameterSet
          Class for the AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet of an AlphabetContainer.
static class AlphabetContainerParameterSet.AlphabetArrayParameterSet
          Class for the parameters of an array of Alphabets of defined length.
static class AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
          Class for the parameter set of an array of Alphabets where each Alphabet may be used for one or more sections of positions.
 

Uses of Storable in de.jstacs.data.alphabets
 

Classes in de.jstacs.data.alphabets that implement Storable
 class ComplementableDiscreteAlphabet
          This abstract class indicates that an alphabet can be used to compute the complement.
 class ContinuousAlphabet
          Class for a continuous alphabet.
static class ContinuousAlphabet.ContinuousAlphabetParameterSet
          Class for the ParameterSet of a ContinuousAlphabet.
 class DiscreteAlphabet
          Class for an alphabet that consists of arbitrary Strings.
static class DiscreteAlphabet.DiscreteAlphabetParameterSet
          Class for the ParameterSet of a DiscreteAlphabet.
 class DNAAlphabet
          This class implements the discrete alphabet that is used for DNA.
static class DNAAlphabet.DNAAlphabetParameterSet
          The parameter set for a DNAAlphabet.
 

Uses of Storable in de.jstacs.data.sequences.annotation
 

Classes in de.jstacs.data.sequences.annotation that implement Storable
 class CisRegulatoryModuleAnnotation
          Annotation for a cis-regulatory module as defined by a set of MotifAnnotations of the motifs in the module.
 class IntronAnnotation
          Annotation class for an intron as defined by a donor and an acceptor splice site.
 class LocatedSequenceAnnotation
          Class for a SequenceAnnotation that has a position on the sequence, e.g for transcription start sites or intron-exon junctions.
 class LocatedSequenceAnnotationWithLength
          Class for a SequenceAnnotation that has a position on the sequence and a length, e.g. for donor splice sites, exons or genes.
 class MotifAnnotation
          Class for a StrandedLocatedSequenceAnnotationWithLength that is a motif.
 class SequenceAnnotation
          Class for a general annotation of a Sequence.
 class SinglePositionSequenceAnnotation
          Class for some annotations that consist mainly of one position on a sequence.
 class StrandedLocatedSequenceAnnotationWithLength
          Class for a SequenceAnnotation that has a position, a length and an orientation on the strand of a Sequence.
 

Uses of Storable in de.jstacs.io
 

Methods in de.jstacs.io that return Storable
static Storable[][] XMLParser.extractStorable2ArrayForTag(StringBuffer source, String tag)
          Returns the value between equal start and end tags as a two dimensional Storable array.
static Storable[][] XMLParser.extractStorable2ArrayForTag(StringBuffer source, String startTag, String endTag)
          Returns the value between start and end tag as a two dimensional Storable array.
static Storable[][][] XMLParser.extractStorable3ArrayForTag(StringBuffer source, String tag)
          Returns the value between equal start and end tags as a three dimensional Storable array.
static Storable[][][] XMLParser.extractStorable3ArrayForTag(StringBuffer source, String startTag, String endTag)
          Returns the value between start and end tag as a three dimensional Storable array.
static Storable[] XMLParser.extractStorableArrayForTag(StringBuffer source, String startTag)
          Returns the value between equal start and end tags as a Storable array.
static Storable[] XMLParser.extractStorableArrayForTag(StringBuffer source, String startTag, String endTag)
          Returns the value between start and end tag as a Storable array.
static Storable XMLParser.extractStorableForTag(StringBuffer source, String startTag)
          Returns the value between equal start and end tags as Storable.
static Storable XMLParser.extractStorableForTag(StringBuffer source, String startTag, String endTag)
          Returns the value between start and end tag as Storable.
static Storable XMLParser.extractStorableOrNullForTag(StringBuffer source, String tag)
          Returns the value between equal start and end tags as Storable or null.
static Storable XMLParser.extractStorableOrNullForTag(StringBuffer source, String startTag, String endTag)
          Returns the value between start and end tag as Storable or null.
 

Methods in de.jstacs.io with parameters of type Storable
static void XMLParser.appendStorable2ArrayWithTags(StringBuffer source, Storable[][] s, String tag)
          Appends an encoded two dimensional Storable array with equal tags to the StringBuffer source.
static void XMLParser.appendStorable2ArrayWithTags(StringBuffer source, Storable[][] s, String startTag, String endTag)
          Appends an encoded two dimensional Storable array with start and end tag to the StringBuffer source.
static void XMLParser.appendStorable3ArrayWithTags(StringBuffer source, Storable[][][] s, String tag)
          Appends an encoded three dimensional Storable array with equal tags to the StringBuffer source.
static void XMLParser.appendStorable3ArrayWithTags(StringBuffer source, Storable[][][] s, String startTag, String endTag)
          Appends an encoded three dimensional Storable array with start and end tag to the StringBuffer source.
static void XMLParser.appendStorableArrayWithTags(StringBuffer source, Storable[] s, String tag)
          Appends an encoded Storable array with equal tags to the StringBuffer source.
static void XMLParser.appendStorableArrayWithTags(StringBuffer source, Storable[] s, String startTag, String endTag)
          Appends an encoded Storable array with start and end tag to the StringBuffer source.
static void XMLParser.appendStorableOrNullWithTags(StringBuffer source, Storable s, String tag)
          Appends a Storable object or "null" with equal tags to the StringBuffer source.
static void XMLParser.appendStorableOrNullWithTags(StringBuffer source, Storable s, String startTag, String endTag)
          Appends a Storable object or "null" with start and end tag to the StringBuffer source.
static void XMLParser.appendStorableWithTags(StringBuffer source, Storable s, String startTag)
          Appends a Storable object with equal tags to the StringBuffer source.
static void XMLParser.appendStorableWithTags(StringBuffer source, Storable s, String startTag, String endTag)
          Appends a Storable object with start and end tag to the StringBuffer source.
protected static StringBuffer XMLParser.StorableArrayWithTags(Storable[] s)
          Encodes a Storable array.
 

Uses of Storable in de.jstacs.models
 

Subinterfaces of Storable in de.jstacs.models
 interface Model
          This interface defines all methods for a probabilistic model.
 

Classes in de.jstacs.models that implement Storable
 class AbstractModel
          Abstract class for a model for pattern recognition.
 class CompositeModel
          This class is for modelling sequences by modelling the different positions of the each sequence by different models.
 class UniformModel
          This class represents a uniform model.
 

Uses of Storable in de.jstacs.models.discrete
 

Classes in de.jstacs.models.discrete that implement Storable
 class Constraint
          The main class for all constraints on models.
 class DGMParameterSet
          The super ParameterSet for any parameter set of a DiscreteGraphicalModel.
 class DiscreteGraphicalModel
          This is the main class for all discrete graphical models (DGM).
 

Uses of Storable in de.jstacs.models.discrete.homogeneous
 

Classes in de.jstacs.models.discrete.homogeneous that implement Storable
 class HomogeneousMM
          This class implements homogeneous Markov models (hMM) of arbitrary order.
 class HomogeneousModel
          This class implements homogeneous models of arbitrary order.
protected  class HomogeneousModel.HomCondProb
          This class handles the (conditional) probabilities of a homogeneous model in a fast way.
 

Uses of Storable in de.jstacs.models.discrete.homogeneous.parameters
 

Classes in de.jstacs.models.discrete.homogeneous.parameters that implement Storable
 class HomMMParameterSet
          This class implements a container for all parameters of a homogeneous Markov model.
 class HomogeneousModelParameterSet
          This class implements a container for all parameters of any homogeneous model.
 

Uses of Storable in de.jstacs.models.discrete.inhomogeneous
 

Classes in de.jstacs.models.discrete.inhomogeneous that implement Storable
 class BayesianNetworkModel
          The class implements a Bayesian network ( StructureLearner.ModelType.BN ) of fixed order.
 class DAGModel
          The abstract class for directed acyclic graphical models (DAGModel).
 class FSDAGModel
          This class can be used for any discrete fixed structure directed acyclic graphical model ( FSDAGModel).
 class InhCondProb
          This class handles (conditional) probabilities of sequences for ihnhomogeneous models.
 class InhConstraint
          This class is the superclass for all inhomogeneous constraints.
 class InhomogeneousDGM
          This class is the main class for all inhomogeneous discrete graphical models (InhomogeneousDGM).
 class MEMConstraint
          This constraint can be used for any maximum entropy model (MEM) application.
 

Uses of Storable in de.jstacs.models.discrete.inhomogeneous.parameters
 

Classes in de.jstacs.models.discrete.inhomogeneous.parameters that implement Storable
 class BayesianNetworkModelParameterSet
          The ParameterSet for the class BayesianNetworkModel.
 class FSDAGMParameterSet
          The class for the parameters of a FSDAGModel (fixed structure directed acyclic graphical model).
 class IDGMParameterSet
          This is the abstract container of parameters that is a root container for all inhomogeneous discrete graphical model parameter containers.
 

Uses of Storable in de.jstacs.models.discrete.inhomogeneous.shared
 

Classes in de.jstacs.models.discrete.inhomogeneous.shared that implement Storable
 class SharedStructureClassifier
          This class enables you to learn the structure on all classes of the classifier together.
 class SharedStructureMixture
          This class handles a mixture of models with the same structure that is learned via EM.
 

Uses of Storable in de.jstacs.models.mixture
 

Classes in de.jstacs.models.mixture that implement Storable
 class AbstractMixtureModel
          This is the abstract class for all kinds of mixture models.
 class MixtureModel
          The class for a mixture model of any Models.
 class StrandModel
          This model handles sequences that can either lie on the forward strand or on the backward strand.
 

Uses of Storable in de.jstacs.models.mixture.gibbssampling
 

Classes in de.jstacs.models.mixture.gibbssampling that implement Storable
 class AbstractBurnInTest
          This abstract class implements some of the methods of BurnInTest to alleviate the implementation of efficient and new burn-in tests.
 class BurnInTest
          This is the abstract super class for any test of the length of the burn-in phase.
 class FSDAGModelForGibbsSampling
          This is the class for a fixed structure directed acyclic graphical model (see FSDAGModel) that can be used in a Gibbs sampling.
 class FSDAGModelForGibbsSamplingParameterSet
          The class for the parameters of a FSDAGModelForGibbsSampling.
 class SimpleBurnInTest
          This is a very simple test for the length of the burn-in phase.
 class VarianceRatioBurnInTest
          In this class the Variance-Ratio method of Gelman and Rubin is implemented to test the length of the burn-in phase of a multi-chain Gibbs Sampling (number of chains >2).
 

Uses of Storable in de.jstacs.models.mixture.motif
 

Classes in de.jstacs.models.mixture.motif that implement Storable
 class HiddenMotifMixture
          This is the main class that every generative motif discoverer should implement.
 class SingleHiddenMotifMixture
          This class enables the user to search for a single motif in a sequence.
 

Uses of Storable in de.jstacs.models.mixture.motif.positionprior
 

Classes in de.jstacs.models.mixture.motif.positionprior that implement Storable
 class GaussianLikePositionPrior
          This class implements a gaussian like discrete truncated prior.
 class PositionPrior
          This is the main class for any position prior that can be used in a motif discovery.
 class UniformPositionPrior
          This prior implements a uniform distribution for the start position.
 

Uses of Storable in de.jstacs.motifDiscovery
 

Subinterfaces of Storable in de.jstacs.motifDiscovery
 interface MotifDiscoverer
          This is the interface that any tool for de-novo motif discovery should implement.
 interface MutableMotifDiscoverer
          This is the interface that any tool for de-novo motif discovery should implement that allows any modify-operations like shift, shrink and expand.
 

Uses of Storable in de.jstacs.parameters
 

Classes in de.jstacs.parameters that implement Storable
 class ArrayParameterSet
          Class for a ParameterSet that consists of a length-Parameter that defines the length of the array and an array of ParameterSetContainers of this length.
 class CollectionParameter
          Class for a collection parameter, i.e. a parameter that provides some collection of possible values the user can choose from.
 class EnumParameter
          This class implements a CollectionParameter based on an Enum.
 class ExpandableParameterSet
          A class for a ParameterSet that can be expanded by additional Parameters at runtime.
 class FileParameter
          Class for a Parameter that represents a local file.
static class FileParameter.FileRepresentation
          Class that represents a file.
 class InstanceParameterSet
          Container class for a set of Parameters that can be used to instantiate another class.
 class MultiSelectionCollectionParameter
          Class for a Parameter that provides a collection of possible values.
 class Parameter
          Abstract class for a parameter that shall be used as the parameter of some method, constructor, etc.
 class ParameterSet
          (Container) class for a set of Parameters.
 class ParameterSetContainer
          Class for a ParameterSetContainer that contains a ParameterSet as value.
 class RangeParameter
          Class for a parameter wrapper that allows SimpleParameters to be set to a set of values.
 class SequenceScoringParameterSet
          Abstract class for a ParameterSet containing all parameters necessary to construct an Object that implements InstantiableFromParameterSet.
 class SimpleParameter
          Class for a "simple" parameter.
 class SimpleParameterSet
          Class for a ParameterSet that is constructed from an array of Parameters and thus does nothing in the method SimpleParameterSet.loadParameters().
 

Uses of Storable in de.jstacs.parameters.validation
 

Subinterfaces of Storable in de.jstacs.parameters.validation
 interface Constraint
          Interface for a constraint that must be fulfilled in a ConstraintValidator.
 interface ParameterValidator
          Interface for a parameter validator, i.e. a class that can validate some possible parameter values.
 

Classes in de.jstacs.parameters.validation that implement Storable
 class ConstraintValidator
          Class for a ParameterValidator that is based on Constraints.
 class NumberValidator<E extends Comparable<? extends Number>>
          Class that validates all subclasses of Number that implement Comparable (e.g.
 class ReferenceConstraint
          Class for a Constraint that defines a condition on one Parameter (the one containing the ConstraintValidator) with respect to another Parameter.
 class SimpleReferenceConstraint
          Class for a ReferenceConstraint that checks for "simple" conditions as defined in the interface Constraint.
 class SimpleStaticConstraint
          Class for a Constraint that checks values against static values using the comparison operators defined in the interface Constraint.
 class StorableValidator
          Class for a validator that validates instances and XML representations for the correct class types (e.g.
 

Constructor parameters in de.jstacs.parameters.validation with type arguments of type Storable
StorableValidator(Class<? extends Storable> clazz)
          Creates a new StorableValidator for a subclass of Storable.
StorableValidator(Class<? extends Storable> clazz, boolean trained)
          Creates a new StorableValidator for a subclass of AbstractModel or AbstractClassifier.
 

Uses of Storable in de.jstacs.results
 

Classes in de.jstacs.results that implement Storable
 class CategoricalResult
          A class for categorical results (i.e. non-numerical results) for primitives and Strings.
 class ImageResult
          A class for results that are images of the PNG format.
 class ListResult
          Class for a Result that contains a list or a matrix, respectively, of ResultSets.
 class MeanResultSet
          Class that computes the mean and the standard error of a series of NumericalResultSets.
 class NumericalResult
          Class for numerical Result values.
 class NumericalResultSet
          Class for a set of numerical result values, which are all of the type NumericalResult.
 class Result
          The abstract class for any result.
 class ResultSet
          Class for a set of Results which provides methods to access single Results in the set, to retrieve the number of Results in the set, to get a String representation or an XML representation of all the Results in the set.
 class SampleResult
          Result that contains a Sample.
 class SimpleResult
          Abstract class for a Result with a value of a primitive data type or String.
 class StorableResult
          Class for Results that are Storables.
 

Methods in de.jstacs.results that return Storable
 Storable StorableResult.getResultInstance()
          Returns the instance of the Storable that is the result of this StorableResult.
 

Constructors in de.jstacs.results with parameters of type Storable
StorableResult(String name, String comment, Storable object)
          Creates a result for an XML representation of an object.
 

Uses of Storable in de.jstacs.scoringFunctions
 

Subinterfaces of Storable in de.jstacs.scoringFunctions
 interface NormalizableScoringFunction
          The interface for normalizable ScoringFunctions.
 interface ScoringFunction
          This interface is the main part of any ScoreClassifier.
 

Classes in de.jstacs.scoringFunctions that implement Storable
 class AbstractNormalizableScoringFunction
          This class is the main part of any ScoreClassifier.
 class IndependentProductScoringFunction
          This class enables the user to model parts of a sequence independent of each other.
 class MRFScoringFunction
          This class implements the scoring function for any MRF (Markov Random Field).
 class NormalizedScoringFunction
          This class makes an unnormalized ScoringFunction to a normalized ScoringFunction.
 class UniformScoringFunction
          This ScoringFunction does nothing.
 class VariableLengthScoringFunction
          This is the main class for all ScoringFunctions that allow to score subsequences of arbitrary length.
 

Uses of Storable in de.jstacs.scoringFunctions.directedGraphicalModels
 

Classes in de.jstacs.scoringFunctions.directedGraphicalModels that implement Storable
 class BayesianNetworkScoringFunction
          This class implements a scoring function that is a moral directed graphical model, i.e. a moral Bayesian network.
 class BayesianNetworkScoringFunctionParameterSet
          Class for the parameters of a BayesianNetworkScoringFunction.
 class MutableMarkovModelScoringFunction
          This class implements a NormalizableScoringFunction for an inhomogeneous Markov model.
 

Uses of Storable in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures
 

Classes in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures that implement Storable
 class InhomogeneousMarkov
          Class for a network structure of a BayesianNetworkScoringFunction that is an inhomogeneous Markov model.
static class InhomogeneousMarkov.InhomogeneousMarkovParameterSet
          Class for an InstanceParameterSet that defines the parameters of an InhomogeneousMarkov structure Measure.
 class Measure
          Class for structure measures that derive an optimal structure with respect to some criterion within a class of possible structures from data.
 

Uses of Storable in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures
 

Classes in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.btMeasures that implement Storable
 class BTExplainingAwayResidual
          Structure learning Measure that computes a maximum spanning tree based on the explaining away residual and uses the resulting tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a BayesianNetworkScoringFunction .
static class BTExplainingAwayResidual.BTExplainingAwayResidualParameterSet
          Class for the parameters of a BTExplainingAwayResidual structure Measure.
 class BTMutualInformation
          Structure learning Measure that computes a maximum spanning tree based on mutual information and uses the resulting tree structure as structure of a Bayesian tree (special case of a Bayesian network) in a BayesianNetworkScoringFunction .
static class BTMutualInformation.BTMutualInformationParameterSet
          Class for the parameters of a BTMutualInformation structure Measure.
 

Uses of Storable in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures
 

Classes in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures that implement Storable
 class PMMExplainingAwayResidual
          Class for the network structure of a BayesianNetworkScoringFunction that is a permuted Markov model based on the explaining away residual.
static class PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
          Class for the parameters of a PMMExplainingAwayResidual structure Measure.
 class PMMMutualInformation
          Class for the network structure of a BayesianNetworkScoringFunction that is a permuted Markov model based on mutual information.
static class PMMMutualInformation.PMMMutualInformationParameterSet
          Class for the parameters of a PMMMutualInformation structure Measure.
 

Uses of Storable in de.jstacs.scoringFunctions.homogeneous
 

Classes in de.jstacs.scoringFunctions.homogeneous that implement Storable
 class HMM0ScoringFunction
          This scoring function implements a homogeneous Markov model of order zero (hMM(0)) for a fixed sequence length.
 class HMMScoringFunction
          This scoring function implements a homogeneous Markov model of arbitrary order for any sequence length.
 class HomogeneousScoringFunction
          This is the main class for all homogeneous ScoringFunctions.
 class UniformHomogeneousScoringFunction
          This scoring function does nothing.
 

Uses of Storable in de.jstacs.scoringFunctions.mix
 

Classes in de.jstacs.scoringFunctions.mix that implement Storable
 class AbstractMixtureScoringFunction
          This main abstract class for any mixture scoring function (e.g.
 class MixtureScoringFunction
          This class implements a real mixture model.
 class StrandScoringFunction
          This class enables the user to search on both strand.
 

Uses of Storable in de.jstacs.scoringFunctions.mix.motifSearch
 

Classes in de.jstacs.scoringFunctions.mix.motifSearch that implement Storable
 class DurationScoringFunction
          This class is the super class for all one dimensional position scoring functions that can be used as durations for semi Markov models.
 class HiddenMotifsMixture
          This class handles mixtures with at least one hidden motif.
 class PositionScoringFunction
          This class implements a position scoring function that enables the user to get a score without using a Sequence object.
 class SkewNormalLikeScoringFunction
          This class implements a skew normal like discrete truncated distribution.
 class UniformDurationScoringFunction
          This scoring function implements a uniform distribution for positions.
 

Uses of Storable in de.jstacs.utils
 

Classes in de.jstacs.utils that implement Storable
 class DoubleList
          A simple list of primitive type double.