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Packages that use gov.sandia.cognition.statistics  

gov.sandia.cognition.learning.algorithm.bayes  Provides algorithms for computing Bayesian categorizers. 
gov.sandia.cognition.learning.algorithm.ensemble  Provides ensmble 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  

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  

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  

ComputableDistribution
A type of Distribution that has an associated distribution function, either a PDF or PMF. 

Distribution
Describes a very highlevel 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  

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  

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 highlevel 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  

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  

CumulativeDistributionFunction
Functionality of a cumulative distribution function. 
Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.statistics  

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 closedform Distribution that also has an associated distribution function. 

ClosedFormCumulativeDistributionFunction
Functionality of a cumulative distribution function that's defined with closedform 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 closedform 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 highlevel distribution of data. 

DistributionEstimator
A BatchLearner that estimates a Distribution. 

DistributionParameter
Allows access to a parameter within a closedform distribution, given by the highlevel String value. 

DistributionWithMean
A Distribution that has a welldefined mean, or first central moment. 

EstimableDistribution
A Distribution that has an estimator associated with it, typically a closedform estimator. 

IncrementalEstimator
An estimator of a Distribution that uses SufficientStatistic to arrive at its result. 

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 closedform 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. 

UnivariateRandomVariable
This is an implementation of a RandomVariable for scalar distributions. 
Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.statistics.bayesian  

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 highlevel distribution of data. 

DistributionParameter
Allows access to a parameter within a closedform distribution, given by the highlevel 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  

ClosedFormDistribution
Defines a distribution that is described a parameterized mathematical equation. 

DistributionParameter
Allows access to a parameter within a closedform distribution, given by the highlevel String value. 
Classes in gov.sandia.cognition.statistics used by gov.sandia.cognition.statistics.distribution  

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, closedform Distribution with a PMF. 

ClosedFormComputableDistribution
A closedform Distribution that also has an associated distribution function. 

ClosedFormCumulativeDistributionFunction
Functionality of a cumulative distribution function that's defined with closedform 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 closedform 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 highlevel 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 welldefined mean, or first central moment. 

EstimableDistribution
A Distribution that has an estimator associated with it, typically a closedform estimator. 

IncrementalEstimator
An estimator of a Distribution that uses SufficientStatistic to arrive at its result. 

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 closedform 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  

ClosedFormComputableDistribution
A closedform 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 closedform 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  

Distribution
Describes a very highlevel 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). 


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