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## P

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 intervall [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 intervall [lower,upper].
Parameter - Class in de.jstacs.parameters
  Abstract class for a parameter that shall be used as the parameter of some method, constructor, etc.
Parameter() - Constructor for class de.jstacs.parameters.Parameter
  Creates a new `Parameter` and generates the internal id.
Parameter - Class in de.jstacs.scoringFunctions.directedGraphicalModels
  Class for the parameters of a `BayesianNetworkScoringFunction`.
Parameter(int, byte, int, double, boolean) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Creates a new parameter, that is parameter no `index` in the list of parameters of the `BayesianNetworkScoringFunction` and responsible for `symbol` at position `position` and pseudo count `pseudoCount`.
Parameter(int, byte, int, int[][], double, boolean) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Creates a new parameter, that is parameter no `index` in the list of parameters of the `BayesianNetworkScoringFunction` and responsible for `symbol` at position `position` having context `context` and pseudo count `pseudoCount`.
Parameter(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  Re-creates a parameter from its XML-representation as returned by the `Parameter.toXML()`} method.
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 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.alphabets.DiscreteAlphabet
  The `ParameterSet` describing this `DiscreteAlphabet`
parameters - Variable in class de.jstacs.parameters.CollectionParameter
  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.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
  The parameters of the scoring function.
ParameterSet - Class in de.jstacs.parameters
  (Container) class for a set of `Parameter`s.
ParameterSet(Class) - Constructor for class de.jstacs.parameters.ParameterSet
  Constructs a `ParameterSet` from the class that can be instantiated using this `ParameterSet`.
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 parameters.
ParameterSet(ArrayList<Parameter>) - Constructor for class de.jstacs.parameters.ParameterSet
  Constructs a `ParameterSet` out of an `ArrayList` of parameters.
ParameterSet(StringBuffer) - Constructor for class de.jstacs.parameters.ParameterSet
  Constructs a `ParameterSet` out of an XML representation
ParameterSet.ParameterList - Class in de.jstacs.parameters
  Class for a `List` of `Parameter`s that basically has the same functionality as `ArrayList`, but additionally takes care of the references `Parameter.parent`.
ParameterSet.ParameterList() - Constructor for class de.jstacs.parameters.ParameterSet.ParameterList
  Creates a new, empty `ParameterSet.ParameterList`.
ParameterSet.ParameterList(Collection<? extends Parameter>) - Constructor for class de.jstacs.parameters.ParameterSet.ParameterList
  Creates a new `ParameterSet.ParameterList` from an existing `Collection` of `Parameter`s.
ParameterSet.ParameterList(int) - Constructor for class de.jstacs.parameters.ParameterSet.ParameterList
  Creates a new, empty `ParameterSet.ParameterList` with a defined initial capacity.
ParameterSetContainer - Class in de.jstacs.parameters
  Class for a `Parameter` that contains a `ParameterSet` as value.
ParameterSetContainer(String, String, ParameterSet) - Constructor for class de.jstacs.parameters.ParameterSetContainer
  Creates an new `ParameterSetContainer` out of a `ParameterSet`.
ParameterSetContainer(StringBuffer) - Constructor for class de.jstacs.parameters.ParameterSetContainer
  Creates a new `ParameterSetContainer` from its XML-representation.
ParameterSetParser - Class in de.jstacs.io
  Class that extracts values from `Parameter`s und 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 `NotInstantiableException` from an error-message.
ParameterSetParser.WrongParameterTypeException - Exception in de.jstacs.io
  An 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 `WrongParameterTypeException` from an error-message
parametersLoaded() - Method in class de.jstacs.parameters.ParameterSet
  Returns `true` if the parameters of this `ParameterSet` have already been loaded using the `loadParameters()`-method
ParameterTree - Class in de.jstacs.scoringFunctions.directedGraphicalModels
  Class for the tree that represents the context of a `Parameter` in a `BayesianNetworkScoringFunction`.
ParameterTree(int, int[], AlphabetContainer, int, int[]) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
  Creates a new `ParameterTree` for the parameters at position `pos` using the parent positions in `contextPoss`.
ParameterTree(StringBuffer, AlphabetContainer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
  Re-creates a `ParameterTree` from its XML-representation as returned by `ParameterTree.toXML()`.
ParameterValidator - Interface in de.jstacs.parameters.validation
  Interface for a parameter validator, i.e. a class that can validate some possible parameter value.
paramRef - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This array contains the references/indices for the parameters.
params - Variable in class de.jstacs.classifier.scoringFunctionBased.ScoreClassifier
  The parameter set for the classifier.
params - Variable in class de.jstacs.models.discrete.DiscreteGraphicalModel
  The current parameter set of the model
paramsFile - Variable in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
  The files for saving the parameters while 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
  Is this `ParameterSet` is contained in a `ParameterSetContainer`, this variable holds a reference to that `ParameterSetContainer`.
parseNextParameterSet() - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  This method allows the user to parse the next set of parameters (from a file).
parseNextParameterSet() - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
parseNextParameterSet() - Method in interface de.jstacs.models.mixture.gibbssampling.GibbsSamplingComponent
  This method allows the user to parse the next set of parameters (from a file).
parseParameterSet(int, int) - Method in class de.jstacs.models.mixture.AbstractMixtureModel
  This method allows the user to parse the set of parameters with index `burnInIteration` of a specific `sampling` (from a file).
parseParameterSet(int, int) - Method in class de.jstacs.models.mixture.gibbssampling.FSDAGModelForGibbsSampling
parseParameterSet(int, int) - Method in interface de.jstacs.models.mixture.gibbssampling.GibbsSamplingComponent
  This method allows the user to parse the set of parameters with index `n` of a certain `sampling` (from a file).
parseSections(String) - Static method in class de.jstacs.data.AlphabetContainerParameterSet.SectionDefinedAlphabetParameterSet
  Parsed the sections as defined in `sections` to a list of `Integer`s.
partition(double, Sample.PartitionMethod, int) - Method in class de.jstacs.data.Sample
  This method partitions the elements of the sample in `2` distinct parts.
partition(Sample.PartitionMethod, double...) - Method in class de.jstacs.data.Sample
  This method partitions the elements of the sample in distinct parts.
partition(int, Sample.PartitionMethod) - Method in class de.jstacs.data.Sample
  This method partitions the elements of the sample in `k` distinct parts.
partNorm - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This array contains the partial normalization constants, i.e. the normalization constant for each component.
PermutedSequence - Class in de.jstacs.data.sequences
  Class for a permuted sequence.
PermutedSequence(Sequence) - Constructor for class de.jstacs.data.sequences.PermutedSequence
  This constructor creates an instance by shuffling the symbols.
plot(REnvironment, AbstractScoreBasedClassifier.DoubleTableResult...) - Static method in class de.jstacs.classifier.AbstractScoreBasedClassifier.DoubleTableResult
  This method plots an array of `DoubleTableResult` in one image
plot(String) - Method in class de.jstacs.utils.REnvironment
  Creates a buffered image form a given plot command.
plot(String, double, double) - Method in class de.jstacs.utils.REnvironment
  Creates a buffered image with given dimension form a given plot command.
plotScores(AbstractScoreBasedClassifier, Sample, Sample, REnvironment, int, double, String) - Static method in class de.jstacs.classifier.utils.ClassificationVisualizer
  This method returns an ImageResult containing a plot of the histograms of the scores.
plotScores(AbstractScoreBasedClassifier, Sample, Sample, REnvironment, int, double, String, String) - Static method in class de.jstacs.classifier.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 form a given plot command.
plotToPDF(String, double, double, String, boolean) - Method in class de.jstacs.utils.REnvironment
  Creates a pdf file with given dimension form a given plot command.
plotToTexFile(String, String, boolean) - Method in class de.jstacs.utils.REnvironment
  Creates a tex file form a given plot command.
plotToTexFile(String, double, double, String, boolean) - Method in class de.jstacs.utils.REnvironment
  Creates a tex file with given dimension form a given plot command.
plugIn - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This boolean indicates whether to use a plug-in strategy to initialize the instance.
plugInParameters - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
  Indicates if plug-in parameters, i.e. generative (MAP) parameters shall be used upon initialization
PMMExplainingAwayResidual - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures
  Class for the network structure of a `BayesianNetworkScoringFunction` that is a permuted Markov model based on the explaining away residual.
PMMExplainingAwayResidual(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
  Re-creates a `PMMExplainingAwayResidual` from its XML-representation as returned by `PMMExplainingAwayResidual.toXML()`.
PMMExplainingAwayResidual(byte, double[]) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMExplainingAwayResidual
  Creates a new `PMMExplainingAwayResidual` of order `order`.
PMMMutualInformation - Class in de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures
  Class for the network structure of a `BayesianNetworkScoringFunction` that is a permuted Markov model based on mutual information.
PMMMutualInformation(byte, int, double[]) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
  Creates a new `PMMMutualInformation` of order `order`.
PMMMutualInformation(StringBuffer) - Constructor for class de.jstacs.scoringFunctions.directedGraphicalModels.structureLearning.measures.pmmMeasures.PMMMutualInformation
  Re-creates a `PMMMutualInformation` from its XML-representation as returned by `PMMMutualInformation.toXML()`.
position - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  The position of `symbol` this parameter is responsible for.
powers - Variable in class de.jstacs.algorithms.graphs.tensor.Tensor
precomputeNorm() - Method in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  Precomutes the normalisation constant.
precomputeNormalization() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
  Precomputes all normalization constants and saves the global normalization constant to `BayesianNetworkScoringFunction.normalizationConstant`.
prepareAssessment(Sample...) - Method in class de.jstacs.classifier.assessment.ClassifierAssessment
  Prepares an assessment.
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.scoringFunctions.directedGraphicalModels.Parameter
  Prints the counts and the value of this parameter to `System.out`.
print() - Method in class de.jstacs.scoringFunctions.directedGraphicalModels.ParameterTree
  Prints the structure of this tree.
prior - Variable in class de.jstacs.classifier.scoringFunctionBased.cll.CLLClassifier
  The prior that is used in this instance.
ProgressUpdater - Interface in de.jstacs.utils
  Interface for supervising the progress of long time processes like cross validation.
propagateId() - Method in class de.jstacs.parameters.ParameterSet
  Propagates the id of this `ParameterSet` to all `Parameter`s above and below in the hierarchy.
pseudoCount - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.Parameter
  The pseudo count for this parameter.
PValueComputation - Class in de.jstacs.classifier.utils
  This class can be used to compute any p-value from a given statistic.
PValueComputation() - Constructor for class de.jstacs.classifier.utils.PValueComputation

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