Uses of Package
gov.sandia.cognition.statistics

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 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
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 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
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 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.
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.
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.
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 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
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
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.
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
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
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).