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

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IDGMParameterSet - Class in de.jstacs.models.discrete.inhomogeneous.parameters
This is the abstract container of parameters that is root container for all inhomogeneous discrete graphical model parameter containers.
IDGMParameterSet(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.parameters.IDGMParameterSet
The constructor for the Storable interface.
IDGMParameterSet(Class<? extends InhomogeneousDGM>) - Constructor for class de.jstacs.models.discrete.inhomogeneous.parameters.IDGMParameterSet
This constructor creates an empty parameter set instance for the specified class.
IDGMParameterSet(Class<? extends InhomogeneousDGM>, AlphabetContainer, int, double, String) - Constructor for class de.jstacs.models.discrete.inhomogeneous.parameters.IDGMParameterSet
This constructor creates a parameter set instance for the specified class.
ignoresCase() - Method in class de.jstacs.data.AlphabetContainer
If this method returns true all used alphabets ignore the case.
ignoresCase() - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
If this method returns true the alphabet ignores the case.
iList - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This array contains some IntLists that are used while computing the partial derivation
ImageResult - Class in de.jstacs.results
A class for results that are images of the PNG format.
ImageResult(String, String, BufferedImage) - Constructor for class de.jstacs.results.ImageResult
Constructs a new ImageResult from a BufferedImage.
IndependentProductScoringFunction - Class in de.jstacs.scoringFunctions
This class enables the user to model parts of the sequence independent of each other.
IndependentProductScoringFunction(NormalizableScoringFunction...) - Constructor for class de.jstacs.scoringFunctions.IndependentProductScoringFunction
This constructor creates an instance of a given series of independent NormalizableScoringFunctions.
IndependentProductScoringFunction(NormalizableScoringFunction[], int[]) - Constructor for class de.jstacs.scoringFunctions.IndependentProductScoringFunction
This constructor creates an instance of a given series of independent NormalizableScoringFunctions and lengths.
IndependentProductScoringFunction(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.IndependentProductScoringFunction
This is the constructor for Storable.
InhCondProb - Class in de.jstacs.models.discrete.inhomogeneous
This class handles the (conditional) probabilities.
InhCondProb(int, int...) - Constructor for class de.jstacs.models.discrete.inhomogeneous.InhCondProb
 
InhCondProb(int[], int[], boolean) - Constructor for class de.jstacs.models.discrete.inhomogeneous.InhCondProb
 
InhCondProb(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.InhCondProb
The constructor for saved objects.
InhConstraint - Class in de.jstacs.models.discrete.inhomogeneous
This class is the super class for all inhomogeneous constraints.
InhConstraint(int[], int[]) - Constructor for class de.jstacs.models.discrete.inhomogeneous.InhConstraint
 
InhConstraint(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.InhConstraint
The constructor for saved objects.
InhomogeneousDGM - Class in de.jstacs.models.discrete.inhomogeneous
This class is the main class for all inhomgeneous discrete graphical models (IDGM).
InhomogeneousDGM(IDGMParameterSet) - Constructor for class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
The default constructor.
InhomogeneousDGM(StringBuffer) - Constructor for class de.jstacs.models.discrete.inhomogeneous.InhomogeneousDGM
This is the constructor for Storable.
InhomogeneousMarkov - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures
Class for a network structure of a BayesianNetworkScoringFunction that is an inhomogeneous Markov model.
InhomogeneousMarkov(int) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
Creates the structure of an inhomogeneous Markov model of order order.
InhomogeneousMarkov(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
Re-creates an InhomogeneousMarkov structure from its XML-representation as returned by InhomogeneousMarkov.toXML().
init(boolean) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method creates the underlying structure for the parameters.
initialIteration - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
The number of initial iterations.
initializeFunction(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
 
initializeFunction(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
 
initializeFunction(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
 
initializeFunction(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
 
initializeFunction(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
 
initializeFunction(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
 
initializeFunction(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
 
initializeFunction(int, boolean, Sample[], double[][]) - Method in interface de.jstacs.scoringFunctions.ScoringFunction
This method creates the underlying structure of the scoring function.
initializeFunction(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
 
initializeFunctionRandomly(boolean) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
 
initializeFunctionRandomly(boolean) - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
 
initializeFunctionRandomly(boolean) - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
 
initializeFunctionRandomly(boolean) - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
 
initializeFunctionRandomly(boolean) - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
 
initializeFunctionRandomly(boolean) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
 
initializeFunctionRandomly(boolean) - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
 
initializeFunctionRandomly(boolean) - Method in interface de.jstacs.scoringFunctions.ScoringFunction
This method initializes the scoring function randomly.
initializeFunctionRandomly(boolean) - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
 
initializeHiddenPotentialRandomly() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method initializes the hidden potential (and the corresponding parameters) randomly.
initializeHiddenUniformly() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method initializes the hidden parameters of the instance uniformly.
initializeMyParametersArrayList() - Method in class de.jstacs.classifier.assessment.ClassifierAssessmentAssessParameterSet
Initializes the list of Parameters in this ParameterSet.
initializeMyParametersArrayList() - Method in class de.jstacs.classifier.assessment.KFoldCVAssessParameterSet
 
initializeMyParametersArrayList() - Method in class de.jstacs.classifier.assessment.RepeatedHoldOutAssessParameterSet
 
initializeMyParametersArrayList() - Method in class de.jstacs.classifier.assessment.RepeatedSubSamplingAssessParameterSet
 
initializeMyParametersArrayList() - Method in class de.jstacs.classifier.assessment.Sampled_RepeatedHoldOutAssessParameterSet
 
initializeRandomly(double) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Initializes the parameters of this ParameterTree randomly
initializeUsingPlugIn(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method initializes the function using the data in some way.
initializeUsingPlugIn(int, boolean, Sample[], double[][]) - Method in class de.jstacs.scoringFunctions.mix.MixtureScoringFunction
 
initModelForSampling(int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method initializes the model for the sampling.
initModelForSampling(int) - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
 
initModelForSampling(int) - Method in interface de.jstacs.models.mixture.gibbssampling.GibbsSamplingComponent
This method initializes the model for the sampling.
initParameterList() - Method in class de.jstacs.parameters.ParameterSet
Initializes the internal set of Parameters, which is a ParameterSet.ParameterList.
initParameterList(int) - Method in class de.jstacs.parameters.ParameterSet
Initializes the internal set of Parameters, which is a ParameterSet.ParameterList, with an initial number of Parameters of initCapacity.
initWithLength(boolean, int) - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This method is used to create the underlying structure, e.g.
initWithPrior(double[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method sets the initial weights before counting the usage of each component.
insertAlphabet(AlphabetContainer, Alphabet, boolean[]) - Static method in class de.jstacs.data.AlphabetContainer
This method may be used to construct a new AlphabetContainer by incorporating additional alphabets into an exsisting AlphabetContainer.
insertProbs(double[]) - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Computes the probabilities for a PWM, i.e. the parameters in the tree have an empty context, and inserts them into probs.
installRScript(String, String, RConnection) - Static method in class de.jstacs.utils.RUtils
Installs an R script on the Rserve server Do not forget to remove the R script by RConnection.removeFile(targetName) at the end of your session.
installScript(String, String, boolean) - Method in class de.jstacs.utils.REnvironment
Installs a script on the server.
InstanceParameterSet - Class in de.jstacs.parameters
Abstract class for a ParameterSet containing all parameters necessary to construct an Object that implements InstantiableFromParameterSet.
InstanceParameterSet(Class, boolean, boolean) - Constructor for class de.jstacs.parameters.InstanceParameterSet
Constructs a InstanceParameterSet having empty parameter values.
InstanceParameterSet(Class, boolean, boolean, boolean) - Constructor for class de.jstacs.parameters.InstanceParameterSet
Constructs a InstanceParameterSet having empty parameter values.
InstanceParameterSet(StringBuffer) - Constructor for class de.jstacs.parameters.InstanceParameterSet
Constructs a InstanceParameterSet from its XML-representation.
InstanceParameterSet(Class, AlphabetContainer, int, boolean) - Constructor for class de.jstacs.parameters.InstanceParameterSet
Constructs a InstanceParameterSet from the alphabet and the length.
InstanceParameterSet(Class, AlphabetContainer) - Constructor for class de.jstacs.parameters.InstanceParameterSet
Constructs a InstanceParameterSet for an object that can handle sequences of variable length and with the alphabet.
InstantiableFromParameterSet - Interface in de.jstacs
Interface for all classes that can be instantiated from a ParameterSet.
IntArrayWithTags(int[]) - Static method in class de.jstacs.io.XMLParser
Encodes an int array.
intersection(Sample...) - Static method in class de.jstacs.data.Sample
This method computes the intersection between all elements of the array, i.e.
IntList - Class in de.jstacs.utils
A simple list of primitive type int.
IntList() - Constructor for class de.jstacs.utils.IntList
This is the default constructor that creates an IntList with initial length 10.
IntList(int) - Constructor for class de.jstacs.utils.IntList
This is the default constructor that creates an IntList with initial length size.
IntronAnnotation - Class in de.jstacs.data.sequences.annotation
Annotation class for an intron as defined by a donor and an acceptor splice site.
IntronAnnotation(String, SinglePositionSequenceAnnotation, SinglePositionSequenceAnnotation, Result...) - Constructor for class de.jstacs.data.sequences.annotation.IntronAnnotation
Creates a new IntronAnnotation from a donor SinglePositionSequenceAnnotation and an acceptor SinglePositionSequenceAnnotation and a set of additional annotations.
IntronAnnotation(StringBuffer) - Constructor for class de.jstacs.data.sequences.annotation.IntronAnnotation
Re-creates an IntronAnnotation from its XML-representation as returned by LocatedSequenceAnnotationWithLength.toXML().
IntSequence - Class in de.jstacs.data.sequences
This class can be used for discrete AlphabetContainer with alphabets that use a huge number of symbols.
IntSequence(AlphabetContainer, int[]) - Constructor for class de.jstacs.data.sequences.IntSequence
This constructor is designed for Model.emitSample(int, int...).
IntSequence(AlphabetContainer, int[], int, int) - Constructor for class de.jstacs.data.sequences.IntSequence
This constructor creates an instance from a part of the content.
IntSequence(AlphabetContainer, String) - Constructor for class de.jstacs.data.sequences.IntSequence
Creates a new sequence from a string representation using the default delimiter.
IntSequence(AlphabetContainer, SequenceAnnotation[], String, String) - Constructor for class de.jstacs.data.sequences.IntSequence
Creates a new sequence from a string representation using the delimiter delim.
IntSequence(AlphabetContainer, SequenceAnnotation[], SymbolExtractor) - Constructor for class de.jstacs.data.sequences.IntSequence
Creates a new sequence from a SymbolExctractor.
invalidateNormalizers() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
Resets all internal normalization constants
invalidateNormalizers() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Resets all pre-computed normalization constants.
isAtomic() - Method in class de.jstacs.parameters.CollectionParameter
Returns true if the collection is of an atomic data type
isAtomic() - Method in class de.jstacs.parameters.FileParameter
 
isAtomic() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
isAtomic() - Method in class de.jstacs.parameters.Parameter
Returns true if the parameter is of an atomic data type
isAtomic() - Method in class de.jstacs.parameters.ParameterSet
Returns true if this ParameterSet contains only atomic parameters, i.e. the parameters do not contain ParameterSets themselves.
isAtomic() - Method in class de.jstacs.parameters.ParameterSetContainer
 
isAtomic() - Method in class de.jstacs.parameters.RangeParameter
 
isAtomic() - Method in class de.jstacs.parameters.SimpleParameter
 
isCancelled() - Method in class de.jstacs.utils.DefaultProgressUpdater
 
isCancelled() - Method in class de.jstacs.utils.GUIProgressUpdater
 
isCancelled() - Method in class de.jstacs.utils.NullProgressUpdater
Returns always false to continue the crossvalidation used with this NullProgressUpdater.
isCancelled() - Method in interface de.jstacs.utils.ProgressUpdater
is the process cancelled by the user
isCancelled() - Method in class de.jstacs.utils.TimeLimitedProgressUpdater
 
isCastableResult(Result) - Method in class de.jstacs.results.Result
Returns true if the datatype of test can be casted to that of this instance and both have the same name and comment for the result.
isComparableResult(Result) - Method in class de.jstacs.results.Result
Returns true if test and the current object have the same datatype, name and comment for the result.
isDiscrete() - Method in class de.jstacs.data.AlphabetContainer
If this method returns true all postions use discrete values.
isDiscrete() - Method in class de.jstacs.data.AlphabetContainerParameterSet
If this method returns true all postions use DiscreteAlphabetParameterSets.
isDiscreteAt(int) - Method in class de.jstacs.data.AlphabetContainer
Returns true if position pos is a discrete random variable.
isDiscreteSample() - Method in class de.jstacs.data.Sample
This method returns true all positions use discrete values.
isEncodedSymbol(int, double) - Method in class de.jstacs.data.AlphabetContainer
Returns true if continuous is a symbol of the alphabet used in position pos.
isEncodedSymbol(double) - Method in class de.jstacs.data.alphabets.ContinuousAlphabet
Returns true if candidat is an element of the internal interval.
isEncodedSymbol(int) - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
Returns true if candidate is an element of the internal interval.
isFree() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
Indicates if this parameter is free.
isInitialized() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
 
isInitialized() - Method in class de.jstacs.scoringFunctions.homogeneous.HMM0ScoringFunction
 
isInitialized() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
 
isInitialized() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
 
isInitialized() - Method in class de.jstacs.scoringFunctions.IndependentProductScoringFunction
 
isInitialized() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
 
isInitialized() - Method in class de.jstacs.scoringFunctions.MRFScoringFunction
 
isInitialized() - Method in interface de.jstacs.scoringFunctions.ScoringFunction
This method can be used to determine whether the model is initialized.
isInitialized() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
 
isInSamplingMode() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method returns true if the object is currently used in a sampling, otherwise false.
isInSamplingMode() - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
 
isInSamplingMode() - Method in interface de.jstacs.models.mixture.gibbssampling.GibbsSamplingComponent
This method returns true if the object is currently used in a sampling, otherwise false.
isLeaf() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
Returns true if the random variable of this ParameterTree is a leaf, i.e. it has no children in the network structure of the enclosing BayesianNetworkScoringFunction.
isNormalized() - Method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
 
isNormalized(NormalizableScoringFunction...) - Static method in class de.jstacs.scoringFunctions.AbstractNormalizableScoringFunction
This method checks whether all given NormalizableScoringFunctions are normalized.
isNormalized() - Method in class de.jstacs.scoringFunctions.homogeneous.HMMScoringFunction
 
isNormalized() - Method in class de.jstacs.scoringFunctions.homogeneous.UniformHomogeneousScoringFunction
 
isNormalized - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
This boolean indicates whether this instance is a normalized one or not.
isNormalized() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
 
isNormalized() - Method in interface de.jstacs.scoringFunctions.NormalizableScoringFunction
This method returns whether the implemented score is already normalized to 1.
isNormalized() - Method in class de.jstacs.scoringFunctions.UniformScoringFunction
 
isRangeable() - Method in class de.jstacs.parameters.CollectionParameter
 
isRangeable() - Method in class de.jstacs.parameters.ParameterSetContainer
 
isRangeable() - Method in interface de.jstacs.parameters.Rangeable
Returns true if the parameters can be varied over a range of values.
isRangeable() - Method in class de.jstacs.parameters.SimpleParameter
 
isRanged() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
isRanged() - Method in class de.jstacs.parameters.ParameterSet
 
isRanged() - Method in class de.jstacs.parameters.ParameterSetContainer
 
isRanged() - Method in interface de.jstacs.parameters.RangeIterator
Returns true if this range iterator is ranging over a set of values.
isRanged() - Method in class de.jstacs.parameters.RangeParameter
 
isRequired() - Method in class de.jstacs.parameters.CollectionParameter
 
isRequired() - Method in class de.jstacs.parameters.FileParameter
 
isRequired() - Method in class de.jstacs.parameters.Parameter
Returns true if the parameter is required, false otherwise
isRequired() - Method in class de.jstacs.parameters.ParameterSetContainer
 
isRequired() - Method in class de.jstacs.parameters.RangeParameter
 
isRequired() - Method in class de.jstacs.parameters.SimpleParameter
 
isReverseComplementable() - Method in class de.jstacs.data.AlphabetContainer
This method helps to determine if the AlphabectContainer also to compute the reverse complement of a sequence.
isSelected(MeasureParameters.Measure) - Method in class de.jstacs.classifier.MeasureParameters
Returns true if the option sel is selected.
isSelected(String) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
Returns the selection value of the option key
isSelected(int) - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
Returns true if the option at position idx is selected.
isSet() - Method in class de.jstacs.parameters.CollectionParameter
Returns true if this collection parameter was selected by the user.
isSet() - Method in class de.jstacs.parameters.FileParameter
 
isSet() - Method in class de.jstacs.parameters.MultiSelectionCollectionParameter
 
isSet() - Method in class de.jstacs.parameters.Parameter
Returns true if the parameter was set by the user.
isSet() - Method in class de.jstacs.parameters.ParameterSetContainer
 
isSet() - Method in class de.jstacs.parameters.RangeParameter
 
isSet() - Method in class de.jstacs.parameters.SimpleParameter
 
isShiftable() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.InhomogeneousMarkov
 
isShiftable() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.Measure
Indicates if Measure supports shifts.
isSimple() - Method in class de.jstacs.data.AlphabetContainer
This method answers the question whether all random variable are defined over the same range, i.e. all positions use the same (fixed) alphabet.
isSimple() - Method in class de.jstacs.data.AlphabetContainerParameterSet
If this method returns true all postions use the same alphabet.
isSimpleSample() - Method in class de.jstacs.data.Sample
This method answers the question whether all random variable are defined over the same range, i.e. all positions use the same (fixed) alphabet.
isSymbol(String) - Method in class de.jstacs.data.alphabets.DiscreteAlphabet
 
isTrained() - Method in class de.jstacs.classifier.AbstractClassifier
This method the state of the classifier.
isTrained() - Method in class de.jstacs.classifier.MappingClassifier
 
isTrained() - Method in class de.jstacs.classifier.modelBased.ModelBasedClassifier
 
isTrained() - Method in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
 
isTrained() - Method in class de.jstacs.models.CompositeModel
 
isTrained() - Method in class de.jstacs.models.discrete.DiscreteGraphicalModel
 
isTrained() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
 
isTrained() - Method in interface de.jstacs.models.Model
Returns true if the model has been trained successfully, false otherwise.
isTrained() - Method in class de.jstacs.models.UniformModel
Returns true.
isTrained() - Method in class de.jstacs.results.StorableResult
Returns TRUE if the model or classifier was trained when obtaining its XML-representation stored in this ObjectResult, FALSE if it was not, and NA if the object could not be trained anyway.
isTrained - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
Indicates if the instance has been trained
isUserSelected() - Method in class de.jstacs.parameters.CollectionParameter
Returns true if the value was selected by the user.
iterate(Sample, double[], MultivariateRandomGenerator, MRGParams[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method runs the train algorithm for the current model.
iterate(int, double[], MultivariateRandomGenerator, MRGParams[]) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
This method runs the train algorithm for the current model and the internal data set.

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