Uses of Package
gov.sandia.cognition.statistics

Packages that use gov.sandia.cognition.statistics

Package	Description
gov.sandia.cognition.learning.algorithm.bayes	Provides algorithms for computing Bayesian categorizers.
gov.sandia.cognition.learning.algorithm.ensemble	Provides ensemble methods.
gov.sandia.cognition.learning.algorithm.hmm	Provides hidden Markov model (HMM) algorithms.
gov.sandia.cognition.learning.data	Provides data set utilities for learning.
gov.sandia.cognition.learning.function.categorization	Provides functions that output a discrete set of categories.
gov.sandia.cognition.learning.function.cost	Provides cost functions.
gov.sandia.cognition.learning.function.scalar	Provides functions that output real numbers.
gov.sandia.cognition.statistics	Provides the inheritance hierarchy for general statistical methods and distributions.
gov.sandia.cognition.statistics.bayesian	Provides algorithms for computing Bayesian estimates of parameters.
gov.sandia.cognition.statistics.bayesian.conjugate	Provides Bayesian estimation routines based on conjugate prior distribution of parameters of specific conditional distributions.
gov.sandia.cognition.statistics.distribution	Provides statistical distributions.
gov.sandia.cognition.statistics.method	Provides algorithms for evaluating statistical data and conducting statistical inference, particularly frequentist methods.
gov.sandia.cognition.statistics.montecarlo	Provides Monte Carlo procedures for numerical integration and sampling.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.learning.algorithm.bayes

Class and Description
DataDistribution A distribution of data from which we can sample and perform Ring operations.
DistributionEstimator A BatchLearner that estimates a Distribution.
UnivariateProbabilityDensityFunction A PDF that takes doubles as input.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.learning.algorithm.ensemble

Class and Description
DataDistribution A distribution of data from which we can sample and perform Ring operations.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.learning.algorithm.hmm

Class and Description
ComputableDistribution A type of Distribution that has an associated distribution function, either a PDF or PMF.
Distribution Describes a very high-level distribution of data.
ProbabilityFunction 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).

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.learning.data

Class and Description
DataDistribution A distribution of data from which we can sample and perform Ring operations.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.learning.function.categorization

Class and Description
AbstractDistribution Partial implementation of Distribution.
ComputableDistribution A type of Distribution that has an associated distribution function, either a PDF or PMF.
Distribution Describes a very high-level distribution of data.
ProbabilityFunction 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).

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.learning.function.cost

Class and Description
ComputableDistribution A type of Distribution that has an associated distribution function, either a PDF or PMF.
ProbabilityFunction 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).
UnivariateDistribution A Distribution that takes Doubles as inputs and can compute its variance.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.learning.function.scalar

Class and Description
CumulativeDistributionFunction Functionality of a cumulative distribution function.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.statistics

Class and Description
AbstractClosedFormUnivariateDistribution Partial implementation of a ClosedFormUnivariateDistribution.
AbstractDataDistribution An abstract implementation of the DataDistribution interface.
AbstractDistribution Partial implementation of Distribution.
AbstractIncrementalEstimator Partial implementation of IncrementalEstimator.
AbstractRandomVariable Partial implementation of RandomVariable.
AbstractSufficientStatistic Partial implementation of SufficientStatistic
ClosedFormComputableDistribution A closed-form Distribution that also has an associated distribution function.
ClosedFormCumulativeDistributionFunction Functionality of a cumulative distribution function that's defined with closed-form parameters.
ClosedFormDiscreteUnivariateDistribution A ClosedFormUnivariateDistribution that is also a DiscreteDistribution
ClosedFormDistribution Defines a distribution that is described a parameterized mathematical equation.
ClosedFormUnivariateDistribution Defines the functionality associated with a closed-form scalar distribution.
ComputableDistribution A type of Distribution that has an associated distribution function, either a PDF or PMF.
CumulativeDistributionFunction Functionality of a cumulative distribution function.
DataDistribution A distribution of data from which we can sample and perform Ring operations.
DataDistribution.PMF Interface for the probability mass function (PMF) of a data distribution.
DefaultDistributionParameter Default implementation of DistributionParameter using introspection.
DiscreteDistribution A Distribution with a countable domain (input) set.
Distribution Describes a very high-level distribution of data.
DistributionEstimator A BatchLearner that estimates a Distribution.
DistributionParameter Allows access to a parameter within a closed-form distribution, given by the high-level String value.
DistributionWeightedEstimator A BatchLearner that estimates a Distribution from a Collection of weighted data.
DistributionWithMean A Distribution that has a well-defined mean, or first central moment.
EstimableDistribution A Distribution that has an estimator associated with it, typically a closed-form estimator.
EstimableWeightedDistribution A Distribution that has an estimator associated with it, typically a closed-form estimator, that can estimate the distribution from weighted data.
IncrementalEstimator An estimator of a Distribution that uses SufficientStatistic to arrive at its result.
IntegerDistribution Defines a distribution over natural numbers.
ProbabilityDensityFunction Defines a probability density function.
ProbabilityFunction 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 The ProbabilityMassFunction interface defines the functionality of a probability mass function.
RandomVariable 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 Sufficient statistics are the data which are sufficient to store all information to create an underlying parameter, such as a Distribution.
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.
UnivariateDistribution A Distribution that takes Doubles as inputs and can compute its variance.
UnivariateProbabilityDensityFunction A PDF that takes doubles as input.
UnivariateRandomVariable This is an implementation of a RandomVariable for scalar distributions.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.statistics.bayesian

Class and Description
AbstractSufficientStatistic Partial implementation of SufficientStatistic
ClosedFormDistribution Defines a distribution that is described a parameterized mathematical equation.
ComputableDistribution A type of Distribution that has an associated distribution function, either a PDF or PMF.
DataDistribution A distribution of data from which we can sample and perform Ring operations.
DefaultDistributionParameter Default implementation of DistributionParameter using introspection.
Distribution Describes a very high-level distribution of data.
DistributionParameter Allows access to a parameter within a closed-form distribution, given by the high-level String value.
ProbabilityFunction 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).
SufficientStatistic Sufficient statistics are the data which are sufficient to store all information to create an underlying parameter, such as a Distribution.
UnivariateDistribution A Distribution that takes Doubles as inputs and can compute its variance.
UnivariateProbabilityDensityFunction A PDF that takes doubles as input.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.statistics.bayesian.conjugate

Class and Description
ClosedFormDistribution Defines a distribution that is described a parameterized mathematical equation.
DistributionParameter Allows access to a parameter within a closed-form distribution, given by the high-level String value.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.statistics.distribution

Class and Description
AbstractClosedFormIntegerDistribution An abstract class for closed-form integer distributions.
AbstractClosedFormSmoothUnivariateDistribution Partial implementation of SmoothUnivariateDistribution
AbstractClosedFormUnivariateDistribution Partial implementation of a ClosedFormUnivariateDistribution.
AbstractDataDistribution An abstract implementation of the DataDistribution interface.
AbstractDistribution Partial implementation of Distribution.
AbstractIncrementalEstimator Partial implementation of IncrementalEstimator.
AbstractSufficientStatistic Partial implementation of SufficientStatistic
ClosedFormComputableDiscreteDistribution A discrete, closed-form Distribution with a PMF.
ClosedFormComputableDistribution A closed-form Distribution that also has an associated distribution function.
ClosedFormCumulativeDistributionFunction Functionality of a cumulative distribution function that's defined with closed-form parameters.
ClosedFormDiscreteUnivariateDistribution A ClosedFormUnivariateDistribution that is also a DiscreteDistribution
ClosedFormDistribution Defines a distribution that is described a parameterized mathematical equation.
ClosedFormUnivariateDistribution Defines the functionality associated with a closed-form scalar distribution.
ComputableDistribution A type of Distribution that has an associated distribution function, either a PDF or PMF.
CumulativeDistributionFunction Functionality of a cumulative distribution function.
DataDistribution A distribution of data from which we can sample and perform Ring operations.
DataDistribution.PMF Interface for the probability mass function (PMF) of a data distribution.
DiscreteDistribution A Distribution with a countable domain (input) set.
Distribution Describes a very high-level distribution of data.
DistributionEstimator A BatchLearner that estimates a Distribution.
DistributionWeightedEstimator A BatchLearner that estimates a Distribution from a Collection of weighted data.
DistributionWithMean A Distribution that has a well-defined mean, or first central moment.
EstimableDistribution A Distribution that has an estimator associated with it, typically a closed-form estimator.
IncrementalEstimator An estimator of a Distribution that uses SufficientStatistic to arrive at its result.
IntegerDistribution Defines a distribution over natural numbers.
InvertibleCumulativeDistributionFunction A cumulative distribution function that is empirically invertible.
ProbabilityDensityFunction Defines a probability density function.
ProbabilityFunction 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 The ProbabilityMassFunction interface defines the functionality of a probability mass function.
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 Sufficient statistics are the data which are sufficient to store all information to create an underlying parameter, such as a Distribution.
UnivariateDistribution A Distribution that takes Doubles as inputs and can compute its variance.
UnivariateProbabilityDensityFunction A PDF that takes doubles as input.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.statistics.method

Class and Description
ClosedFormComputableDistribution A closed-form Distribution that also has an associated distribution function.
ClosedFormDiscreteUnivariateDistribution A ClosedFormUnivariateDistribution that is also a DiscreteDistribution
ClosedFormDistribution Defines a distribution that is described a parameterized mathematical equation.
CumulativeDistributionFunction Functionality of a cumulative distribution function.
ProbabilityDensityFunction Defines a probability density function.
ProbabilityMassFunction The ProbabilityMassFunction interface defines the functionality of a probability mass function.
SmoothCumulativeDistributionFunction This defines a CDF that has an associated derivative, which is its PDF.
SmoothUnivariateDistribution A closed-form scalar distribution that is also smooth.
UnivariateDistribution A Distribution that takes Doubles as inputs and can compute its variance.

Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.statistics.montecarlo

Class and Description
Distribution Describes a very high-level distribution of data.
ProbabilityDensityFunction Defines a probability density function.
ProbabilityFunction 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).