See: Description
| Interface | Description |
|---|---|
| ClosedFormComputableDiscreteDistribution<DataType> |
A discrete, closed-form Distribution with a PMF.
|
| ClosedFormComputableDistribution<DataType> |
A closed-form Distribution that also has an associated distribution function.
|
| ClosedFormCumulativeDistributionFunction<DomainType extends java.lang.Number> |
Functionality of a cumulative distribution function that's defined with
closed-form parameters.
|
| ClosedFormDiscreteUnivariateDistribution<DomainType extends java.lang.Number> |
A ClosedFormUnivariateDistribution that is also a DiscreteDistribution
|
| ClosedFormDistribution<DataType> |
Defines a distribution that is described a parameterized mathematical
equation.
|
| ClosedFormUnivariateDistribution<NumberType extends java.lang.Number> |
Defines the functionality associated with a closed-form scalar distribution.
|
| ComputableDistribution<DomainType> |
A type of Distribution that has an associated distribution function,
either a PDF or PMF.
|
| CumulativeDistributionFunction<NumberType extends java.lang.Number> |
Functionality of a cumulative distribution function.
|
| DataDistribution<DataType> |
A distribution of data from which we can sample and perform Ring operations.
|
| DataDistribution.PMF<KeyType> |
Interface for the probability mass function (PMF) of a data distribution.
|
| DiscreteDistribution<DataType> |
A Distribution with a countable domain (input) set.
|
| Distribution<DataType> |
Describes a very high-level distribution of data.
|
| DistributionEstimator<ObservationType,DistributionType extends Distribution<? extends ObservationType>> |
A BatchLearner that estimates a Distribution.
|
| DistributionParameter<ParameterType,ConditionalType extends Distribution<?>> |
Allows access to a parameter within a closed-form distribution, given by
the high-level String value.
|
| DistributionWeightedEstimator<ObservationType,DistributionType extends Distribution<? extends ObservationType>> |
A BatchLearner that estimates a Distribution from a Collection of
weighted data.
|
| DistributionWithMean<DataType> |
A Distribution that has a well-defined mean, or first central moment.
|
| EstimableDistribution<ObservationType,DistributionType extends EstimableDistribution<ObservationType,? extends DistributionType>> |
A Distribution that has an estimator associated with it, typically a
closed-form estimator.
|
| EstimableWeightedDistribution<ObservationType,DistributionType extends EstimableWeightedDistribution<ObservationType,? extends DistributionType>> |
A Distribution that has an estimator associated with it, typically a
closed-form estimator, that can estimate the distribution from weighted data.
|
| IncrementalEstimator<DataType,DistributionType extends Distribution<? extends DataType>,SufficientStatisticsType extends SufficientStatistic<? super DataType,? extends DistributionType>> |
An estimator of a Distribution that uses SufficientStatistic to arrive
at its result.
|
| IntegerDistribution |
Defines a distribution over natural numbers.
|
| InvertibleCumulativeDistributionFunction<NumberType extends java.lang.Number> |
A cumulative distribution function that is empirically invertible.
|
| ProbabilityDensityFunction<DataType> |
Defines a probability density function.
|
| ProbabilityFunction<DataType> |
A Distribution that has an evaluate method that indicates p(x), such as
a probability density function or a probability mass function (but NOT
a cumulative distribution function).
|
| ProbabilityMassFunction<DataType> |
The
ProbabilityMassFunction interface defines the functionality of
a probability mass function. |
| RandomVariable<DataType> |
Describes the functionality of a random variable.
|
| SmoothCumulativeDistributionFunction |
This defines a CDF that has an associated derivative, which is its PDF.
|
| SmoothUnivariateDistribution |
A closed-form scalar distribution that is also smooth.
|
| SufficientStatistic<DataType,DistributionType> |
Sufficient statistics are the data which are sufficient to store all
information to create an underlying parameter, such as a Distribution.
|
| UnivariateDistribution<NumberType extends java.lang.Number> |
A Distribution that takes Doubles as inputs and can compute its variance.
|
| UnivariateProbabilityDensityFunction |
A PDF that takes doubles as input.
|
| Class | Description |
|---|---|
| AbstractClosedFormIntegerDistribution |
An abstract class for closed-form integer distributions.
|
| AbstractClosedFormSmoothUnivariateDistribution |
Partial implementation of SmoothUnivariateDistribution
|
| AbstractClosedFormUnivariateDistribution<NumberType extends java.lang.Number> |
Partial implementation of a ClosedFormUnivariateDistribution.
|
| AbstractDataDistribution<KeyType> |
An abstract implementation of the
DataDistribution interface. |
| AbstractDistribution<DataType> |
Partial implementation of Distribution.
|
| AbstractIncrementalEstimator<DataType,DistributionType extends Distribution<? extends DataType>,SufficientStatisticsType extends SufficientStatistic<DataType,DistributionType>> |
Partial implementation of
IncrementalEstimator. |
| AbstractRandomVariable<DataType> |
Partial implementation of RandomVariable.
|
| AbstractSufficientStatistic<DataType,DistributionType> |
Partial implementation of SufficientStatistic
|
| ChiSquaredSimilarity |
A class for computing the chi-squared similarity between two vectors.
|
| DefaultDistributionParameter<ParameterType,ConditionalType extends ClosedFormDistribution<?>> |
Default implementation of DistributionParameter using introspection.
|
| DiscreteSamplingUtil |
A utility class for sampling.
|
| DistributionParameterUtil |
Functions to assist in creating DistributionParameters.
|
| KullbackLeiblerDivergence<DomainType> |
A class used for measuring how similar two distributions are using Kullback--Leibler Divergence.
|
| ProbabilityMassFunctionUtil |
Utility methods for helping computations in PMFs.
|
| TransferEntropy |
A class for calculating the transfer entropy of two vectors.
|
| TransferEntropy.TransferEntropyDistributionObject |
A helper class that define the objects used by the distributions in transfer entropy.
|
| TransferEntropy.TransferEntropyPartialSumObject |
Helper class for holding information about the partial sums.
|
| UnivariateRandomVariable |
This is an implementation of a RandomVariable for scalar distributions.
|