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## P

Pair<E1,E2> - Class in de.jstacs.utils
  A very simple container.
Pair(E1, E2) - Constructor for class de.jstacs.utils.Pair
  This constructor creates a pair of `element1` and `element2`.
PairwiseStringAlignment - Class in de.jstacs.algorithms.alignment
  Class for the representation of an alignment of two `String`s.
PairwiseStringAlignment(String, String, double, int, int) - Constructor for class de.jstacs.algorithms.alignment.PairwiseStringAlignment
  Creates the instance for the two (extended) `String`s and the edit-costs.
parabolicInterpolation(OneDimensionalFunction, double, double, double, double, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
  Approximates a minimum (not necessary the global) in the interval `[lower,upper]`.
parabolicInterpolation(OneDimensionalFunction, double, double, double, double) - Static method in class de.jstacs.algorithms.optimization.Optimizer
  Approximates a minimum (not necessary the global) in the interval `[lower,upper]`.
parameter - Variable in class de.jstacs.algorithms.optimization.termination.AbstractTerminationCondition
  The internally used parameters.
Parameter - Class in de.jstacs.parameters
  Abstract class for a parameter that shall be used as the parameter of some method, constructor, etc.
Parameter(String, String, DataType) - Constructor for class de.jstacs.parameters.Parameter
  The main constructor which takes the main information of a `Parameter`.
Parameter(StringBuffer) - Constructor for class de.jstacs.parameters.Parameter
  The standard constructor for the interface `Storable`.
ParameterException - Exception in de.jstacs.parameters
  Class for an exception that is thrown if some error occurs while setting a parameter's value or constructing a parameter.
ParameterException(String) - Constructor for exception de.jstacs.parameters.ParameterException
  Constructor for a `ParameterException` with the specified error message.
ParameterException() - Constructor for exception de.jstacs.parameters.ParameterException
  Constructor for a `ParameterException` without a specific message.
parameterRemovable() - Method in class de.jstacs.parameters.ExpandableParameterSet
  Returns `true` if there is still a `Parameter` that can be removed from the set.
parameters - Variable in class de.jstacs.data.AlphabetContainer
  The parameters for this instance.
parameters - Variable in class de.jstacs.data.alphabets.DiscreteAlphabet
  The parameter set describing this `DiscreteAlphabet` .
parameters - Variable in class de.jstacs.parameters.AbstractSelectionParameter
  The internal `ParameterSet` that holds the possible values
parameters - Variable in class de.jstacs.parameters.ParameterSet
  The set of parameters
parameters - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
  The parameters of the scoring function.
parameters - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.Measure
  The parameters of this measure
parameters - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  The parameters defining the distribution over all states that can be visited.
ParameterSet - Class in de.jstacs.parameters
  (Container) class for a set of `Parameter`s.
ParameterSet() - Constructor for class de.jstacs.parameters.ParameterSet
  Constructs a new `ParameterSet` with empty parameter values.
ParameterSet(Parameter[]) - Constructor for class de.jstacs.parameters.ParameterSet
  Constructs a `ParameterSet` out of an array of `Parameter`s.
ParameterSet(ArrayList<Parameter>) - Constructor for class de.jstacs.parameters.ParameterSet
  Constructs a `ParameterSet` out of an `ArrayList` of `Parameter`s.
ParameterSet(StringBuffer) - Constructor for class de.jstacs.parameters.ParameterSet
  The standard constructor for the interface `Storable`.
ParameterSet.ParameterList - Class in de.jstacs.parameters
  Class for a `AnnotatedEntityList` that automatically sets the `Parameter.parent` field to the enclosing `ParameterSet`.
ParameterSet.ParameterList() - Constructor for class de.jstacs.parameters.ParameterSet.ParameterList
ParameterSet.ParameterList(int) - Constructor for class de.jstacs.parameters.ParameterSet.ParameterList
ParameterSetContainer - Class in de.jstacs.parameters
  Class for a `ParameterSetContainer` that contains a `ParameterSet` as value.
ParameterSetContainer(ParameterSet) - Constructor for class de.jstacs.parameters.ParameterSetContainer
  Creates an new `ParameterSetContainer` out of a `ParameterSet`.
ParameterSetContainer(String, String, ParameterSet) - Constructor for class de.jstacs.parameters.ParameterSetContainer
  Creates an new `ParameterSetContainer` out of a `ParameterSet`.
ParameterSetContainer(Class<? extends ParameterSet>) - Constructor for class de.jstacs.parameters.ParameterSetContainer
  Creates an new `ParameterSetContainer` out of the class of a `ParameterSet`.
ParameterSetContainer(String, String, Class<? extends ParameterSet>) - Constructor for class de.jstacs.parameters.ParameterSetContainer
  Creates an new `ParameterSetContainer` out of the class of a `ParameterSet`.
ParameterSetContainer(StringBuffer) - Constructor for class de.jstacs.parameters.ParameterSetContainer
  The standard constructor for the interface `Storable`.
ParameterSetParser - Class in de.jstacs.io
  This class extracts values from `Parameter`s and creates instances of `InstantiableFromParameterSet`s from a `ParameterSet`.
ParameterSetParser() - Constructor for class de.jstacs.io.ParameterSetParser
ParameterSetParser.NotInstantiableException - Exception in de.jstacs.io
  An `Exception` that is thrown if an instance of some class could not be created.
ParameterSetParser.NotInstantiableException(String) - Constructor for exception de.jstacs.io.ParameterSetParser.NotInstantiableException
  Creates a new instance of a `ParameterSetParser.NotInstantiableException` with a given error message.
ParameterSetParser.WrongParameterTypeException - Exception in de.jstacs.io
  An `Exception` that is thrown if the `DataType` of a `Parameter` is not appropriate for some purpose.
ParameterSetParser.WrongParameterTypeException(String) - Constructor for exception de.jstacs.io.ParameterSetParser.WrongParameterTypeException
  Creates a new instance of a `ParameterSetParser.WrongParameterTypeException` with a given error message.
ParameterSetTagger - Class in de.jstacs.parameters
  This class implements a tagger for `Parameter` of `ParameterSet`.
ParameterSetTagger(String[], ParameterSet...) - Constructor for class de.jstacs.parameters.ParameterSetTagger
  The constructor creates an new instance by collecting and tagging all parameters of the `ParameterSet`s.
ParameterSetTagger.KeyEntryComparator<K extends Comparable<K>,V> - Class in de.jstacs.parameters
  This class implements a comparator on `Map.Entry` that sorts by the key of the `Map.Entry`.
ParameterSetTagger.KeyEntryComparator() - Constructor for class de.jstacs.parameters.ParameterSetTagger.KeyEntryComparator
  Creates a `Comparator` that only compares the keys of `Map.Entry`s.
ParameterSetTagger.RankEntryComparator<K,V> - Class in de.jstacs.parameters
  This class implements a comparator on `Map.Entry` where value is a `ComparableElement` with weight `Integer`.
ParameterSetTagger.RankEntryComparator() - Constructor for class de.jstacs.parameters.ParameterSetTagger.RankEntryComparator
  Creates a `Comparator` that only compares the ranks of `Map.Entry`s where the rank is determined by the `ParameterSet.parameters`.
parametersLoaded() - Method in class de.jstacs.parameters.ParameterSet
  Returns `true` if the parameters of this `ParameterSet` have been loaded.
ParameterValidator - Interface in de.jstacs.parameters.validation
  Interface for a parameter validator, i.e. a class that can validate some possible parameter values.
paramRef - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
  This array contains the references/indices for the parameters.
params - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.AbstractMultiThreadedOptimizableFunction
  This is a pointer for the current parameters.
params - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
  Parameters
params - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
  The parameter set for the classifier.
params - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.DiscreteGraphicalTrainSM
  The current parameter set of the model.
params - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  The parameters of the emission
paramsFile - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
  The files for saving the parameters during the sampling.
paramsFile - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  The files for saving the parameters during the sampling.
paramsFile - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
  The files for saving the parameters during the sampling.
parent - Variable in class de.jstacs.parameters.Parameter
  If this `Parameter` is enclosed in a `ParameterSet`, this variable holds a reference to that `ParameterSet`.
parent - Variable in class de.jstacs.parameters.ParameterSet
  If this `ParameterSet` is contained in a `ParameterSetContainer`, this variable holds a reference to that `ParameterSetContainer`.
parse(String[]) - Method in class de.jstacs.utils.galaxy.GalaxyAdaptor
  Parses the command line.
parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.MotifAnnotationParser
parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.NullSequenceAnnotationParser
parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.ReferenceSequenceAnnotationParser
parseAnnotationToComment(char, SequenceAnnotation...) - Method in interface de.jstacs.data.sequences.annotation.SequenceAnnotationParser
  This method returns a `String` representation of the given `SequenceAnnotation`s that can be used as comment line in a file.
parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.SimpleSequenceAnnotationParser
parseAnnotationToComment(char, SequenceAnnotation...) - Method in class de.jstacs.data.sequences.annotation.SplitSequenceAnnotationParser
parseHashSet2IndexHashtable(HashSet<K>) - Static method in class de.jstacs.utils.ToolBox
  This method converts a `HashSet` in a `Hashtable` with unique indices starting at 0.
parseNextParameterSet() - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier.DiffSMSamplingComponent
parseNextParameterSet() - Method in interface de.jstacs.sampling.SamplingComponent
  This method allows the user to parse the next set of parameters (from a file).
parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
  This method parse a parameter set stored in file during sampling
parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleSamplingState
parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
parseNextParameterSet() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  This method allows the user to parse the next set of parameters (from a file).
parseParameterSet(int, int) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier.DiffSMSamplingComponent
parseParameterSet(int, int) - Method in interface de.jstacs.sampling.SamplingComponent
  This method allows the user to parse the set of parameters with index `n` of a certain `sampling` (from a file).
parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.inhomogeneous.FSDAGModelForGibbsSampling
parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.SamplingHigherOrderHMM
  This method allows the user to parse the set of parameters with index `idx` of a certain `sampling` (from a file).
parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.SilentEmission
parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.SimpleSamplingState
parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.HigherOrderTransition
parseParameterSet(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.AbstractMixtureTrainSM
  This method allows the user to parse the set of parameters with index `burnInIteration` of a specific `sampling` (from a file).
parseSections(String) - Static method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
  Parses the sections as defined in `sections` to a `LinkedList` of `Integer`s.
parseString(String) - Static method in class de.jstacs.io.XMLParser
  This method parses the `original` `String` to `null` if `original` equals "null".
partDerState - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
  Help array for the derivatives of the parameters of the states
partDerTransition - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.models.DifferentiableHigherOrderHMM
  Help array for the derivatives of the parameters of the transition
partialLength - Variable in class de.jstacs.sequenceScores.differentiable.IndependentProductDiffSS
  This array specifies the lengths of the specific parts.
partition(double, DataSet.PartitionMethod, int) - Method in class de.jstacs.data.DataSet
  This method partitions the elements, i.e. the `Sequence`s, of the `DataSet` in two distinct parts.
partition(DataSet.PartitionMethod, double...) - Method in class de.jstacs.data.DataSet
  This method partitions the elements, i.e. the `Sequence`s, of the `DataSet` in distinct parts where each part holds the corresponding percentage given in the array `percentage`.
partition(double[], DataSet.PartitionMethod, double...) - Method in class de.jstacs.data.DataSet
  This method partitions the elements, i.e. the `Sequence`s, of the `DataSet` and the corresponding weights in distinct parts where each part holds the corresponding percentage given in the array `percentage`.
partition(int, DataSet.PartitionMethod) - Method in class de.jstacs.data.DataSet
  This method partitions the elements, i.e. the `Sequence`s, of the `DataSet` in `k` distinct parts.
partition(double[], int, DataSet.PartitionMethod) - Method in class de.jstacs.data.DataSet
  This method partitions the elements, i.e. the `Sequence`s, of the `DataSet` and the corresponding weights in `k` distinct parts.
partNorm - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
  This array contains the partial normalization constants, i.e. the normalization constant for each component.
pearsonCorrelation(double[], double[]) - Static method in class de.jstacs.utils.ToolBox
  The method computes the Pearson correlation of two vectors.
PerformanceMeasureParameterSet - Class in de.jstacs.classifiers.performanceMeasures
  This class implements a container of `AbstractPerformanceMeasure`s that can be used in `AbstractClassifier.evaluate(PerformanceMeasureParameterSet, boolean, de.jstacs.data.DataSet...)`.
PerformanceMeasureParameterSet(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
  The standard constructor for the interface `Storable`.
PerformanceMeasureParameterSet() - Constructor for class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
  Constructs a new `PerformanceMeasureParameterSet` that can be used for binary classifiers.
PerformanceMeasureParameterSet(int) - Constructor for class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
  Constructs a new `PerformanceMeasureParameterSet` that can be used for classifiers that handle the given number of classes.
PerformanceMeasureParameterSet(AbstractPerformanceMeasure...) - Constructor for class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
  Constructs a new `PerformanceMeasureParameterSet` with the given performance measures.
PerformanceMeasureParameterSet(int, SelectionParameter, AbstractPerformanceMeasure...) - Constructor for class de.jstacs.classifiers.performanceMeasures.PerformanceMeasureParameterSet
  This constructor creates an instance with a given template `selection` that can be used for classifiers handling a given number of classes.
PermutedSequence<T> - Class in de.jstacs.data.sequences
  This class is for permuted sequences.
PermutedSequence(Sequence<T>) - Constructor for class de.jstacs.data.sequences.PermutedSequence
  Creates a new `PermutedSequence` by shuffling the symbols of a given `Sequence`.
PermutedSequence(Sequence<T>, int[]) - Constructor for class de.jstacs.data.sequences.PermutedSequence
  Creates a new `PermutedSequence` for a given permutation
PhyloDiscreteEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete
  Phylogenetic discrete emission This class uses a phylogenetic tree to describe multidimensional data It implements Felsensteins model for nucleotide substitution (F81)
PhyloDiscreteEmission(AlphabetContainer, double, PhyloTree) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
  This is a simple constructor for a `PhyloDiscreteEmission` based on the equivalent sample size.
PhyloDiscreteEmission(AlphabetContainer, double[], PhyloTree) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.PhyloDiscreteEmission
  This is a simple constructor for a `DiscreteEmission` defining the individual hyper parameters.
PhyloNode - Class in de.jstacs.sequenceScores.statisticalModels.trainable.phylo
  This class implements a node in a `PhyloTree` A PhyloNode contains some basic informations of itself and the incoming edge Furthermore it contains a list of `PhyloNode`s that represent the children nodes
PhyloNode() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
  Basic constructor
PhyloNode(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloNode
  The standard constructor for the interface `Storable`.
PhyloTree - Class in de.jstacs.sequenceScores.statisticalModels.trainable.phylo
  This class implements a simple (phylogenetic) tree.
PhyloTree(String, PhyloNode) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree
  Construct an instance of the class PhyloTree
PhyloTree(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.phylo.PhyloTree
  The standard constructor for the interface `Storable`.
plot(REnvironment, AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifiers.AbstractScoreBasedClassifier.DoubleTableResult
  This method plots an array of `AbstractScoreBasedClassifier.DoubleTableResult`s in one image.
plot(MotifDiscoverer, int, int, Sequence, int, REnvironment, int, int, MotifDiscoverer.KindOfProfile) - Static method in class de.jstacs.motifDiscovery.MotifDiscovererToolBox
  This method creates a simple plot of the profile of scores for a sequence and a start position.
plot(String) - Method in class de.jstacs.utils.REnvironment
  Creates a buffered image from a given plot command.
plot(String, double, double) - Method in class de.jstacs.utils.REnvironment
  Creates a buffered image with given dimension from a given plot command.
plot(String, double, double, String, OutputStream) - Method in class de.jstacs.utils.REnvironment
  This method creates an image with given dimension from a given plot command and pipes it to the output stream.
plotAndAnnotate(MotifDiscoverer, int, int, Sequence, int, REnvironment, int, int, double, double, double, MotifDiscoverer.KindOfProfile) - Static method in class de.jstacs.motifDiscovery.MotifDiscovererToolBox
  This method creates a plot of the profile of scores for a sequence and a start position and annotates bindings sites in the plot that have a higher score than `threshold`.
plotScores(AbstractScoreBasedClassifier, DataSet, DataSet, REnvironment, int, double, String) - Static method in class de.jstacs.classifiers.utils.ClassificationVisualizer
  This method returns an `ImageResult` containing a plot of the histograms of the scores.
plotScores(AbstractScoreBasedClassifier, DataSet, DataSet, REnvironment, int, double, String, String) - Static method in class de.jstacs.classifiers.utils.ClassificationVisualizer
  This method creates a pdf containing a plot of the histograms of the scores.
plotToPDF(String, String, boolean) - Method in class de.jstacs.utils.REnvironment
  Creates a pdf file from a given plot command.
plotToPDF(String, double, double, String, boolean) - Method in class de.jstacs.utils.REnvironment
  Creates a pdf file with given dimension from a given plot command.
plotToTexFile(String, String, boolean) - Method in class de.jstacs.utils.REnvironment
  Creates a tex file from a given plot command.
plotToTexFile(String, double, double, String, boolean) - Method in class de.jstacs.utils.REnvironment
  Creates a tex file with given dimension from a given plot command.
PluginGaussianEmission - Class in de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous
  Basic Gaussian emission distribution without random initialization of parameters.
PluginGaussianEmission(double, double, double, double, double, double) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.PluginGaussianEmission
  Creates a Gaussian emission density with mean `mean` and standard deviation `sd`.
PluginGaussianEmission(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.PluginGaussianEmission
  Creates a `PluginGaussianEmission` from its XML representation.
plugInParameters - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
  Indicates if plug-in parameters, i.e. generative (MAP) parameters shall be used upon initialization.
PMMExplainingAwayResidual - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
  Class for the network structure of a `BayesianNetworkDiffSM` that is a permuted Markov model based on the explaining away residual.
PMMExplainingAwayResidual(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
  The standard constructor for the interface `Storable`.
PMMExplainingAwayResidual(byte, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
  Creates a new `PMMExplainingAwayResidual` of order `order`.
PMMExplainingAwayResidual(PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
  Creates a new `PMMExplainingAwayResidual` from the corresponding `InstanceParameterSet` `parameters/code>.`
PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
  Class for the parameters of a `PMMExplainingAwayResidual` structure `Measure`.
PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
  Creates a new `PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet` with empty parameter values.
PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet(byte, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
  Creates a new `PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet` with the parameter for the order set to `order` and the parameter for the equivalent sample sizes (ess) set to `ess`.
PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet
  Creates a new `PMMExplainingAwayResidual.PMMExplainingAwayResidualParameterSet` from its XML representation as defined by the `Storable` interface.
PMMMutualInformation - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
  Class for the network structure of a `BayesianNetworkDiffSM` that is a permuted Markov model based on mutual information.
PMMMutualInformation(byte, BTMutualInformation.DataSource, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
  Creates a new `PMMMutualInformation` of order `order`.
PMMMutualInformation(PMMMutualInformation.PMMMutualInformationParameterSet) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
  Creates a new `PMMMutualInformation` from the corresponding `InstanceParameterSet` `parameters`.
PMMMutualInformation(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
  The standard constructor for the interface `Storable`.
PMMMutualInformation.PMMMutualInformationParameterSet - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures
  Class for the parameters of a `PMMMutualInformation` structure `Measure`.
PMMMutualInformation.PMMMutualInformationParameterSet() - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
  Creates a new `PMMMutualInformation.PMMMutualInformationParameterSet` with empty parameter values.
PMMMutualInformation.PMMMutualInformationParameterSet(byte, BTMutualInformation.DataSource, double[]) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
  Creates a new `PMMMutualInformation.PMMMutualInformationParameterSet` with the parameter for the order set to `order`, the parameter for the `BTMutualInformation.DataSource` set to `clazz` and the parameter for the equivalent sample sizes (ess) set to `ess`.
PMMMutualInformation.PMMMutualInformationParameterSet(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation.PMMMutualInformationParameterSet
  Creates a new `PMMMutualInformation.PMMMutualInformationParameterSet` from its XML representation as defined by the `Storable` interface.
position - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
  The position of `symbol` this parameter is responsible for.
PositionDiffSM - Class in de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif
  This class implements a position scoring function that enables the user to get a score without using a Sequence object.
PositionDiffSM(AlphabetContainer, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
  This constructor allows create instance with more than one dimension.
PositionDiffSM(int, int) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
  This is the main constructor that creates the `AlphabetContainer` internally.
PositionDiffSM(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.motif.PositionDiffSM
  This is the constructor for `Storable`.
PositionPrior - Class in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior
  This is the main class for any position prior that can be used in a motif discovery.
PositionPrior() - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
  This empty constructor creates an instance with motif length -1.
PositionPrior(StringBuffer) - Constructor for class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.positionprior.PositionPrior
  The standard constructor for the interface `Storable`.
PositivePredictiveValueForFixedSensitivity - Class in de.jstacs.classifiers.performanceMeasures
  This class implements the positive predictive value for a fixed sensitivity.
PositivePredictiveValueForFixedSensitivity() - Constructor for class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
  Constructs a new instance of the performance measure `PositivePredictiveValueForFixedSensitivity` with empty parameter values.
PositivePredictiveValueForFixedSensitivity(double) - Constructor for class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
  Constructs a new instance of the performance measure `PositivePredictiveValueForFixedSensitivity` with given `sensitivity`.
PositivePredictiveValueForFixedSensitivity(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.PositivePredictiveValueForFixedSensitivity
  The standard constructor for the interface `Storable`.
posPrior - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif.HiddenMotifMixture
  The prior for the positions.
powers - Variable in class de.jstacs.algorithms.graphs.tensor.Tensor
  An array containing the powers for the number of nodes.
powers - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.discrete.homogeneous.HomogeneousTrainSM
  The powers of the alphabet length.
PRCurve - Class in de.jstacs.classifiers.performanceMeasures
  This class implements the precision-recall curve and its area under the curve.
PRCurve() - Constructor for class de.jstacs.classifiers.performanceMeasures.PRCurve
  Constructs a new instance of the performance measure `PRCurve`.
PRCurve(StringBuffer) - Constructor for class de.jstacs.classifiers.performanceMeasures.PRCurve
  The standard constructor for the interface `Storable`.
precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.continuous.GaussianEmission
  This method precomputes some normalization constant.
precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  This method precomputes some normalization constant and probabilities.
precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.BasicHigherOrderTransition.AbstractTransitionElement
  This method precomputes internal fields as for instance the normalization constant.
precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
precompute() - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
precomputeBurnInLength(SamplingScoreBasedClassifier.DiffSMSamplingComponent) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
  Precomputes the length of the burn-in phase, e.g. useful for computing scores of multiple sequences
precomputeNorm() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.mixture.AbstractMixtureDiffSM
  Pre-computes the normalization constant.
precomputeNormalization() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BayesianNetworkDiffSM
  Pre-computes all normalization constants.
preoptimize(OptimizableFunction) - Method in class de.jstacs.classifiers.differentiableSequenceScoreBased.ScoreClassifier
  This method allows to pre-optimize the parameter before the real optimization.
prepareAssessment(DataSet...) - Method in class de.jstacs.classifiers.assessment.ClassifierAssessment
  Prepares an assessment.
previousParameters - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.sampling.SamplingScoreBasedClassifier
  The previously accepted parameters, backup for rollbacks
prGrad - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LogGenDisMixFunction
  Array for the gradient of the prior
print(PrintWriter) - Method in class de.jstacs.results.ListResult
  Prints the information of this `ListResult` to the provided `PrintWriter`.
print() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
  Prints the counts and the value of this parameter to `System.out`.
print() - Method in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree
  Prints the structure of this tree.
prior - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.DiffSSBasedOptimizableFunction
  The prior that is used in this function.
prior - Variable in class de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier
  The prior that is used in this classifier.
PRIOR_INDEX - Static variable in enum de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.LearningPrinciple
  This constant is the array index of the weighting factor for the prior.
probabilities - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.ReferenceBasedTransitionElement
  Represents the initial the transition probabilities.
probs - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.states.emissions.discrete.AbstractConditionalDiscreteEmission
  The parameters transformed to probabilites
probs - Variable in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.transitions.elements.TransitionElement
  The precomputed probabilities for each possible transition.
ProductConstraint - Class in de.jstacs.sequenceScores.differentiable.logistic
  This class implements product constraints, i.e., the method `ProductConstraint.getValue(Sequence,int)` returns the product of the values for the positions defined in the constructor.
ProductConstraint(int...) - Constructor for class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
  This is the main constructor creating an instance from a given set of positions.
ProductConstraint(StringBuffer) - Constructor for class de.jstacs.sequenceScores.differentiable.logistic.ProductConstraint
  This is the constructor for `Storable`.
ProgressUpdater - Interface in de.jstacs.utils
  Interface for supervising the progress of long time processes like cross validation.
propagateESS(double, ArrayList<HMMFactory.PseudoTransitionElement>) - Static method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.HMMFactory
  Propagates the `ess` for an HMM with absorbing states.
ProteinAlphabet - Class in de.jstacs.data.alphabets
  This class implements the discrete alphabet that is used for proteins (one letter code).
ProteinAlphabet.ProteinAlphabetParameterSet - Class in de.jstacs.data.alphabets
  The parameter set for a `ProteinAlphabet`.
provideMatrix(int, int) - Method in class de.jstacs.sequenceScores.statisticalModels.trainable.hmm.AbstractHMM
  This method invokes the method `AbstractHMM.createHelperVariables()` and provides the matrix with given type.
pseudoCount - Variable in class de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter
  The pseudocount for this parameter.
PValueComputation - Class in de.jstacs.classifiers.utils
  This class can be used to compute any p-value from a given statistic.
PValueComputation() - Constructor for class de.jstacs.classifiers.utils.PValueComputation

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