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See:
Description
Interface Summary | |
Distribution | An encapsulation of a probability distribution over the Symbols within an alphabet. |
DistributionFactory | A thing that can make Distributions. |
DistributionTrainer | An object that can be used to train a distribution up. |
DistributionTrainerContext | A context within a group of DistributionTrainers can be trained together. |
Class Summary | |
AbstractDistribution | An abstract implementation of Distribution. |
ComplementaryDistribution | Creates a complementary distribution from a given distribution. |
DistributionFactory.DefaultDistributionFactory | The default DistributionFactory implementation. |
DNADistribution | A state in a markov process. |
GapDistribution | This distribution emits only the gap symbol. |
IgnoreCountsTrainer | A distribution trainer that just ignores all counts. |
PairDistribution | Class for pairing up two unique distributions. |
SimpleDistribution | A simple implementation of a distribution, which works with any finite alphabet. |
SimpleDistributionTrainer | An implemenation of a simple distribution trainer |
SimpleDistributionTrainerContext | A no-frills implementation of DistributionTrainerContext. |
UniformDistribution | An implementation of an uniform distribution |
Probability distributions over Alphabets. Distributions are useful in many aspects of bioinformatics, especially when performing statistical methods. They are used to encapsulate emission spectra in weight matrices and Hidden Markov Models.
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