Package | Description |
---|---|
gov.sandia.cognition.statistics |
Provides the inheritance hierarchy for general statistical methods and 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.
|
Modifier and Type | Interface and Description |
---|---|
interface |
ClosedFormComputableDiscreteDistribution<DataType>
A discrete, closed-form Distribution with a PMF.
|
interface |
ClosedFormDiscreteUnivariateDistribution<DomainType extends java.lang.Number>
A ClosedFormUnivariateDistribution that is also a DiscreteDistribution
|
interface |
SmoothCumulativeDistributionFunction
This defines a CDF that has an associated derivative, which is its PDF.
|
interface |
SmoothUnivariateDistribution
A closed-form scalar distribution that is also smooth.
|
interface |
UnivariateProbabilityDensityFunction
A PDF that takes doubles as input.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractClosedFormIntegerDistribution
An abstract class for closed-form integer distributions.
|
class |
AbstractClosedFormSmoothUnivariateDistribution
Partial implementation of SmoothUnivariateDistribution
|
Modifier and Type | Class and Description |
---|---|
class |
MultivariateMixtureDensityModel<DistributionType extends ClosedFormComputableDistribution<Vector>>
A LinearMixtureModel of multivariate distributions with associated PDFs.
|
static class |
MultivariateMixtureDensityModel.PDF<DistributionType extends ClosedFormComputableDistribution<Vector>>
PDF of the MultivariateMixtureDensityModel
|
Modifier and Type | Class and Description |
---|---|
class |
BernoulliDistribution
A Bernoulli distribution, which takes a value of "1" with probability "p"
and value of "0" with probability "1-p".
|
static class |
BernoulliDistribution.CDF
CDF of a Bernoulli distribution.
|
static class |
BernoulliDistribution.PMF
PMF of the Bernoulli distribution.
|
class |
BetaBinomialDistribution
A Binomial distribution where the binomial parameter, p, is set according
to a Beta distribution instead of a single value.
|
static class |
BetaBinomialDistribution.CDF
CDF of BetaBinomialDistribution
|
static class |
BetaBinomialDistribution.PMF
PMF of the BetaBinomialDistribution
|
class |
BetaDistribution
Computes the Beta-family of probability distributions.
|
static class |
BetaDistribution.CDF
CDF of the Beta-family distribution
|
static class |
BetaDistribution.PDF
Beta distribution probability density function
|
class |
BinomialDistribution
Binomial distribution, which is a collection of Bernoulli trials
|
static class |
BinomialDistribution.CDF
CDF of the Binomial distribution, which is the probability of getting
up to "x" successes in "N" trials with a Bernoulli probability of "p"
|
static class |
BinomialDistribution.PMF
The Probability Mass Function of a binomial distribution.
|
class |
CategoricalDistribution
The Categorical Distribution is the multivariate generalization of the
Bernoulli distribution, where the outcome of an experiment is a one-of-N
output, where the output is a selector Vector.
|
static class |
CategoricalDistribution.PMF
PMF of the Categorical Distribution
|
class |
CauchyDistribution
A Cauchy Distribution is the ratio of two Gaussian Distributions, sometimes
known as the Lorentz distribution.
|
static class |
CauchyDistribution.CDF
CDF of the CauchyDistribution.
|
static class |
CauchyDistribution.PDF
PDF of the CauchyDistribution.
|
class |
ChineseRestaurantProcess
A Chinese Restaurant Process is a discrete stochastic processes that
partitions data points to clusters.
|
static class |
ChineseRestaurantProcess.PMF
PMF of the Chinese Restaurant Process
|
class |
ChiSquareDistribution
Describes a Chi-Square Distribution.
|
static class |
ChiSquareDistribution.CDF
Cumulative Distribution Function (CDF) of a Chi-Square Distribution
|
static class |
ChiSquareDistribution.PDF
PDF of the Chi-Square distribution
|
class |
DeterministicDistribution
A deterministic distribution that returns samples at a single point.
|
static class |
DeterministicDistribution.CDF
CDF of the deterministic distribution.
|
static class |
DeterministicDistribution.PMF
PMF of the deterministic distribution.
|
class |
DirichletDistribution
The Dirichlet distribution is the multivariate generalization of the beta
distribution.
|
static class |
DirichletDistribution.PDF
PDF of the Dirichlet distribution.
|
class |
ExponentialDistribution
An Exponential distribution describes the time between events in a poisson
process, resulting in a memoryless distribution.
|
static class |
ExponentialDistribution.CDF
CDF of the ExponentialDistribution.
|
static class |
ExponentialDistribution.PDF
PDF of the ExponentialDistribution.
|
class |
GammaDistribution
Class representing the Gamma distribution.
|
static class |
GammaDistribution.CDF
CDF of the Gamma distribution
|
static class |
GammaDistribution.PDF
Closed-form PDF of the Gamma distribution
|
class |
GeometricDistribution
The geometric distribution models the number of successes before the first
failure occurs under an independent succession of Bernoulli tests.
|
static class |
GeometricDistribution.CDF
CDF of the Geometric distribution
|
static class |
GeometricDistribution.PMF
PMF of the Geometric distribution
|
class |
InverseGammaDistribution
Defines an inverse-gamma distribution.
|
static class |
InverseGammaDistribution.CDF
CDF of the inverseRootFinder-gamma distribution.
|
static class |
InverseGammaDistribution.PDF
PDF of the inverseRootFinder-Gamma distribution.
|
class |
InverseWishartDistribution
The Inverse-Wishart distribution is the multivariate generalization of the
inverse-gamma distribution.
|
static class |
InverseWishartDistribution.PDF
PDF of the Inverse-Wishart distribution, though I have absolutely no
idea why anybody would evaluate the PDF of an Inverse-Wishart...
|
class |
LaplaceDistribution
A Laplace distribution, sometimes called a double exponential distribution.
|
static class |
LaplaceDistribution.CDF
CDF of the Laplace distribution.
|
static class |
LaplaceDistribution.PDF
The PDF of a Laplace Distribution.
|
class |
LogisticDistribution
A implementation of the scalar logistic distribution, which measures the
log-odds of a binary event.
|
static class |
LogisticDistribution.CDF
CDF of the LogisticDistribution
|
static class |
LogisticDistribution.PDF
PDF of the LogisticDistribution
|
class |
LogNormalDistribution
Log-Normal distribution PDF and CDF implementations.
|
static class |
LogNormalDistribution.CDF
CDF of the Log-Normal Distribution
|
static class |
LogNormalDistribution.PDF
PDF of a Log-normal distribution
|
static class |
MixtureOfGaussians.PDF
PDF of the MixtureOfGaussians
|
class |
MultinomialDistribution
A multinomial distribution is the multivariate/multiclass generalization
of the Binomial distribution.
|
static class |
MultinomialDistribution.PMF
Probability Mass Function of the Multinomial Distribution.
|
class |
MultivariateGaussian
The MultivariateGaussian class implements a multidimensional Gaussian
distribution that contains a mean vector and a covariance matrix.
|
static class |
MultivariateGaussian.PDF
PDF of a multivariate Gaussian
|
class |
MultivariateMixtureDensityModel<DistributionType extends ClosedFormComputableDistribution<Vector>>
A LinearMixtureModel of multivariate distributions with associated PDFs.
|
static class |
MultivariateMixtureDensityModel.PDF<DistributionType extends ClosedFormComputableDistribution<Vector>>
PDF of the MultivariateMixtureDensityModel
|
class |
MultivariatePolyaDistribution
A multivariate Polya Distribution, also known as a Dirichlet-Multinomial
model, is a compound distribution where the parameters of a multinomial
are drawn from a Dirichlet distribution with fixed parameters and a constant
number of trials and then the observations are generated by this
multinomial.
|
static class |
MultivariatePolyaDistribution.PMF
PMF of the MultivariatePolyaDistribution
|
class |
MultivariateStudentTDistribution
Multivariate generalization of the noncentral Student's t-distribution.
|
static class |
MultivariateStudentTDistribution.PDF
PDF of the MultivariateStudentTDistribution
|
class |
NegativeBinomialDistribution
Negative binomial distribution, also known as the Polya distribution,
gives the number of successes of a series of Bernoulli trials before
recording a given number of failures.
|
static class |
NegativeBinomialDistribution.CDF
CDF of the NegativeBinomialDistribution
|
static class |
NegativeBinomialDistribution.PMF
PMF of the NegativeBinomialDistribution.
|
class |
NormalInverseGammaDistribution
The normal inverse-gamma distribution is the product of a univariate
Gaussian distribution with an inverse-gamma distribution.
|
static class |
NormalInverseGammaDistribution.PDF
PDF of the NormalInverseGammaDistribution
|
class |
NormalInverseWishartDistribution
The normal inverse Wishart distribution
|
static class |
NormalInverseWishartDistribution.PDF
PDF of the normal inverse-Wishart distribution.
|
class |
ParetoDistribution
This class describes the Pareto distribution, sometimes called the Bradford
Distribution.
|
static class |
ParetoDistribution.CDF
CDF of the Pareto Distribution.
|
static class |
ParetoDistribution.PDF
PDF of the ParetoDistribution
|
class |
PoissonDistribution
A Poisson distribution is the limits of what happens when a Bernoulli trial
with "rare" events are sampled on a continuous basis and then binned into
discrete time intervals.
|
static class |
PoissonDistribution.CDF
CDF of the PoissonDistribution
|
static class |
PoissonDistribution.PMF
PMF of the PoissonDistribution.
|
class |
ScalarMixtureDensityModel
ScalarMixtureDensityModel (SMDM) implements just that: a scalar mixture density
model.
|
static class |
ScalarMixtureDensityModel.CDF
CDFof the SMDM
|
static class |
ScalarMixtureDensityModel.PDF
PDF of the SMDM
|
class |
StudentTDistribution
Defines a noncentral Student-t Distribution.
|
static class |
StudentTDistribution.CDF
Evaluator that computes the Cumulative Distribution Function (CDF) of
a Student-t distribution with a fixed number of degrees of freedom
|
static class |
StudentTDistribution.PDF
Evaluator that computes the Probability Density Function (CDF) of
a Student-t distribution with a fixed number of degrees of freedom
|
class |
UniformDistribution
Contains the (very simple) definition of a continuous Uniform distribution,
parameterized between the minimum and maximum bounds.
|
static class |
UniformDistribution.CDF
Cumulative Distribution Function of a uniform
|
static class |
UniformDistribution.PDF
Probability density function of a Uniform Distribution
|
class |
UniformIntegerDistribution
Contains the (very simple) definition of a continuous Uniform distribution,
parameterized between the minimum and maximum bounds.
|
static class |
UniformIntegerDistribution.CDF
Implements the cumulative distribution function for the discrete
uniform distribution.
|
static class |
UniformIntegerDistribution.PMF
Probability mass function of a discrete uniform distribution.
|
class |
UnivariateGaussian
This class contains internal classes that implement useful functions based
on the Gaussian distribution.
|
static class |
UnivariateGaussian.CDF
CDF of the underlying Gaussian.
|
static class |
UnivariateGaussian.CDF.Inverse
Inverts the CumulativeDistribution function.
|
static class |
UnivariateGaussian.PDF
PDF of the underlying Gaussian.
|
class |
WeibullDistribution
Describes a Weibull distribution, which is often used to describe the
mortality, lifespan, or size distribution of objects.
|
static class |
WeibullDistribution.CDF
CDF of the Weibull distribution
|
static class |
WeibullDistribution.PDF
PDF of the Weibull distribution
|
class |
YuleSimonDistribution
The Yule-Simon distribution is a model of preferential attachment, such as
a model of the number of groups follows a power-law distribution
(Zipf's Law).
|
static class |
YuleSimonDistribution.CDF
CDF of the Yule-Simon Distribution
|
static class |
YuleSimonDistribution.PMF
PMF of the Yule-Simon Distribution
|
Modifier and Type | Method and Description |
---|---|
protected static <DistributionType extends ClosedFormComputableDistribution<?>> |
MaximumLikelihoodDistributionEstimator.getDistributionClasses(java.lang.Class<? extends DistributionType> baseDistribution)
Gets the distribution classes for the given base distribution.
|
Modifier and Type | Method and Description |
---|---|
ClosedFormComputableDistribution<DataType> |
MaximumLikelihoodDistributionEstimator.learn(java.util.Collection<? extends DataType> data) |
Modifier and Type | Method and Description |
---|---|
Pair<java.lang.Double,ClosedFormComputableDistribution<DataType>> |
MaximumLikelihoodDistributionEstimator.DistributionEstimationTask.call() |
java.util.Collection<? extends ClosedFormComputableDistribution<DataType>> |
MaximumLikelihoodDistributionEstimator.getDistributions()
Getter for distributions
|
Modifier and Type | Method and Description |
---|---|
void |
MaximumLikelihoodDistributionEstimator.setDistributions(java.util.Collection<? extends ClosedFormComputableDistribution<DataType>> distributions)
Setter for distributions
|
Constructor and Description |
---|
DistributionEstimationTask(ClosedFormComputableDistribution<DataType> distribution,
java.util.Collection<? extends DataType> data)
Creates a new instance of DistributionEstimationTask
|
Constructor and Description |
---|
MaximumLikelihoodDistributionEstimator(java.util.Collection<? extends ClosedFormComputableDistribution<DataType>> distributions)
Creates a new instance of MaximumLikelihoodDistributionEstimator
|