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## O

offset - Variable in class de.jstacs.models.discrete.inhomogeneous.InhConstraint
  This array is used to find the start indices of the conditional distributions.
OneDimensionalFunction - Class in de.jstacs.algorithms.optimization
  This class implements the interface `Function` for an one-dimensional function.
OneDimensionalFunction() - Constructor for class de.jstacs.algorithms.optimization.OneDimensionalFunction
OneDimensionalSubFunction - Class in de.jstacs.algorithms.optimization
  This class is used to do the line search.
OneDimensionalSubFunction(Function, double[], double[]) - Constructor for class de.jstacs.algorithms.optimization.OneDimensionalSubFunction
  Creates a new `OneDimensionalSubFunction` from a `Function` `f` for the line search.
openRConnection(String, String, String) - Static method in class de.jstacs.utils.RUtils
  This method opens an `RConnection`.
operationAllowed(int...) - Method in interface de.jstacs.motifDiscovery.history.History
  Returns `true` if the specified operation is allowed, i.e. it does not conflict with any operation from the history.
operationAllowed(int...) - Method in class de.jstacs.motifDiscovery.history.RestrictedRepeatHistory
operationPerfomed(int...) - Method in interface de.jstacs.motifDiscovery.history.History
  This method puts an operation to the history.
operationPerfomed(int...) - Method in class de.jstacs.motifDiscovery.history.RestrictedRepeatHistory
OptimizableFunction - Class in de.jstacs.classifier.scoringFunctionBased
  This is the main function for the `ScoreClassifier`.
OptimizableFunction() - Constructor for class de.jstacs.classifier.scoringFunctionBased.OptimizableFunction
OptimizableFunction.KindOfParameter - Enum in de.jstacs.classifier.scoringFunctionBased
  This `enum` defines the kinds of parameters that can be returned by the method `OptimizableFunction.getParameters(KindOfParameter)`.
optimize(byte, DifferentiableFunction, double[], Optimizer.TerminationCondition, double, double, StartDistanceForecaster, SafeOutputStream) - Static method in class de.jstacs.algorithms.optimization.Optimizer
  This method enables you to use all different implemented optimization algorithms by only one method.
optimize(byte, DifferentiableFunction, double[], Optimizer.TerminationCondition, double, double, StartDistanceForecaster, SafeOutputStream, Time) - Static method in class de.jstacs.algorithms.optimization.Optimizer
  This method enables you to use all different implemented optimization algorithms by only one method.
optimize(ScoringFunction[], OptimizableFunction, byte, double, double, StartDistanceForecaster, SafeOutputStream, boolean, History, OptimizableFunction.KindOfParameter) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
  This method tries to optimize the problem at hand as good as possible.
optimize(ScoringFunction[], OptimizableFunction, byte, double, double, StartDistanceForecaster, SafeOutputStream, boolean, History[][], int[][], OptimizableFunction.KindOfParameter) - Static method in class de.jstacs.motifDiscovery.MutableMotifDiscovererToolbox
  This method tries to optimize the problem at hand as good as possible.
optimizeHidden - Variable in class de.jstacs.scoringFunctions.mix.AbstractMixtureScoringFunction
  This `boolean` indicates whether to optimize the hidden variables of this instance.
optimizeModel - Variable in class de.jstacs.models.mixture.AbstractMixtureModel
  A switch for each model whether to optimize/adjust or not.
Optimizer - Class in de.jstacs.algorithms.optimization
  This class can be used for optimization purposes.
Optimizer() - Constructor for class de.jstacs.algorithms.optimization.Optimizer
Optimizer.TerminationCondition - Enum in de.jstacs.algorithms.optimization
  This `enum` defines all kinds of termination conditions for the `Optimizer`.
order - Variable in class de.jstacs.algorithms.graphs.tensor.Tensor
  The order of the tensor.
order - Variable in class de.jstacs.models.discrete.homogeneous.HomogeneousModel
  The order of the model.
order - Variable in class de.jstacs.scoringFunctions.directedGraphicalModels.BayesianNetworkScoringFunction
  The network structure, used internally.

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