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Packages that use MultivariateRandomGenerator | |
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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 |
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Methods in de.jstacs.sequenceScores.statisticalModels.trainable.mixture that return MultivariateRandomGenerator | |
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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 | |
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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)
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protected double[][] |
MixtureTrainSM.doFirstIteration(double[] dataWeights,
MultivariateRandomGenerator m,
MRGParams[] params)
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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 sample. |
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 |
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Methods in de.jstacs.sequenceScores.statisticalModels.trainable.mixture.motif with parameters of type MultivariateRandomGenerator | |
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protected double[][] |
ZOOPSTrainSM.doFirstIteration(double[] dataWeights,
MultivariateRandomGenerator m,
MRGParams[] params)
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protected double |
ZOOPSTrainSM.iterate(int start,
double[] dataWeights,
MultivariateRandomGenerator m,
MRGParams[] params)
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Uses of MultivariateRandomGenerator in de.jstacs.utils.random |
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Subclasses of MultivariateRandomGenerator in de.jstacs.utils.random | |
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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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