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

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

Uses of MultivariateRandomGenerator in de.jstacs.models.mixture

Methods in de.jstacs.models.mixture that return MultivariateRandomGenerator
`protected MultivariateRandomGenerator` | `AbstractMixtureModel.getMRG()` This method creates the multivariate random generator that will be used during initialization.

Methods in de.jstacs.models.mixture with parameters of type MultivariateRandomGenerator
`protected double[][]` | `StrandModel.doFirstIteration(double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)`
`protected double[][]` | `MixtureModel.doFirstIteration(double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)`
`protected abstract double[][]` | `AbstractMixtureModel.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 sample.
`protected double[][]` | `AbstractMixtureModel.doFirstIteration(Sample data, double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)` This method will do the first step in the train algorithm for the current model.
`protected double` | `AbstractMixtureModel.iterate(int start, double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)` This method runs the train algorithm for the current model and the internal data set.
`double` | `AbstractMixtureModel.iterate(Sample data, double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)` This method runs the train algorithm for the current model.

Uses of MultivariateRandomGenerator in de.jstacs.models.mixture.motif

Methods in de.jstacs.models.mixture.motif with parameters of type MultivariateRandomGenerator
`protected double[][]` | `SingleHiddenMotifMixture.doFirstIteration(double[] dataWeights, MultivariateRandomGenerator m, MRGParams[] params)`
`protected double` | `SingleHiddenMotifMixture.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.

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