Uses of Class
de.jstacs.utils.random.MultivariateRandomGenerator

Packages that use MultivariateRandomGenerator
de.jstacs.sequenceScores.statisticalModels.trainable.mixture This package is the super package for any mixture model. 
de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif   
de.jstacs.utils.random This package contains some classes for generating random numbers. 
 

Uses of MultivariateRandomGenerator in de.jstacs.sequenceScores.statisticalModels.trainable.mixture
 

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.mixture that return MultivariateRandomGenerator
protected  MultivariateRandomGenerator AbstractMixtureTrainSM.getMRG()
          This method creates the multivariate random generator that will be used during initialization.
 

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.mixture with parameters of type MultivariateRandomGenerator
protected  double[][] AbstractMixtureTrainSM.doFirstIteration(DataSet data, double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)
          This method will do the first step in the train algorithm for the current model.
protected  double[][] StrandTrainSM.doFirstIteration(double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)
           
protected  double[][] MixtureTrainSM.doFirstIteration(double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)
           
protected abstract  double[][] AbstractMixtureTrainSM.doFirstIteration(double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)
          This method will do the first step in the train algorithm for the current model on the internal data set.
 double AbstractMixtureTrainSM.iterate(DataSet data, double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)
          This method runs the train algorithm for the current model.
protected  double AbstractMixtureTrainSM.iterate(int start, double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)
          This method runs the train algorithm for the current model and the internal data set.
 

Uses of MultivariateRandomGenerator in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif
 

Methods in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif with parameters of type MultivariateRandomGenerator
protected  double[][] ZOOPSTrainSM.doFirstIteration(double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)
           
protected  double ZOOPSTrainSM.iterate(int start, double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)
           
 

Uses of MultivariateRandomGenerator in de.jstacs.utils.random
 

Subclasses of MultivariateRandomGenerator in de.jstacs.utils.random
 class DirichletMRG
          This class is a multivariate random generator based on a Dirichlet distribution.
 class EqualParts
          This class is no real random generator it just returns 1/n for all values.
 class ErlangMRG
          This class is a multivariate random generator based on a Dirichlet distribution for alpha_i \in N.
 class SoftOneOfN
          This random generator returns 1-epsilon for one and equal parts for the rest of a random vector.