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Interface Summary | |
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Model<O> | A model is a probability distribution over observed data points and allows the probability of any data point to be computed. |
ModelDistribution<O> | A model distribution allows us to sample a model from its prior distribution. |
Class Summary | |
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AsymmetricSampledNormalDistribution | An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
AsymmetricSampledNormalModel | |
L1Model | |
L1ModelDistribution | An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
NormalModel | |
NormalModelDistribution | An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
SampledNormalDistribution | An implementation of the ModelDistribution interface suitable for testing the DirichletCluster algorithm. |
SampledNormalModel | |
VectorModelDistribution |
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