Uses of Interface
gov.sandia.cognition.statistics.SmoothUnivariateDistribution

Packages that use SmoothUnivariateDistribution

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.

Uses of SmoothUnivariateDistribution in gov.sandia.cognition.statistics

Subinterfaces of SmoothUnivariateDistribution in gov.sandia.cognition.statistics

Modifier and Type	Interface and Description
interface	SmoothCumulativeDistributionFunction This defines a CDF that has an associated derivative, which is its PDF.
interface	UnivariateProbabilityDensityFunction A PDF that takes doubles as input.

Classes in gov.sandia.cognition.statistics that implement SmoothUnivariateDistribution

Modifier and Type	Class and Description
class	AbstractClosedFormSmoothUnivariateDistribution Partial implementation of SmoothUnivariateDistribution

Uses of SmoothUnivariateDistribution in gov.sandia.cognition.statistics.distribution

Classes in gov.sandia.cognition.statistics.distribution that implement SmoothUnivariateDistribution

Modifier and Type	Class and Description
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	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	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	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	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	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
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	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	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

Methods in gov.sandia.cognition.statistics.distribution that return types with arguments of type SmoothUnivariateDistribution

Modifier and Type	Method and Description
java.util.Collection<? extends DistributionWeightedEstimator<java.lang.Double,? extends SmoothUnivariateDistribution>>	ScalarMixtureDensityModel.EMLearner.getLearners() Getter for learners

Method parameters in gov.sandia.cognition.statistics.distribution with type arguments of type SmoothUnivariateDistribution

Modifier and Type	Method and Description
void	ScalarMixtureDensityModel.EMLearner.setLearners(java.util.Collection<? extends DistributionWeightedEstimator<java.lang.Double,? extends SmoothUnivariateDistribution>> learners) Setter for learners

Constructors in gov.sandia.cognition.statistics.distribution with parameters of type SmoothUnivariateDistribution

Constructor and Description
CDF(SmoothUnivariateDistribution... distributions) Creates a new instance of ScalarMixtureDensityModel
PDF(SmoothUnivariateDistribution... distributions) Creates a new instance of ScalarMixtureDensityModel
SampleRange(java.util.Random random, int treatmentCount, SmoothUnivariateDistribution t) Creates a new instance of SampleRange
ScalarMixtureDensityModel(SmoothUnivariateDistribution... distributions) Creates a new instance of ScalarMixtureDensityModel

Constructor parameters in gov.sandia.cognition.statistics.distribution with type arguments of type SmoothUnivariateDistribution

Constructor and Description
CDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions) Creates a new instance of ScalarMixtureDensityModel
CDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions, double[] priorWeights) Creates a new instance of ScalarMixtureDensityModel
EMLearner(int numClusters, DistributionWeightedEstimator<java.lang.Double,? extends SmoothUnivariateDistribution> learner, java.util.Random random) Creates a new instance of EMLearner
EMLearner(java.util.Random random, java.util.Collection<? extends DistributionWeightedEstimator<java.lang.Double,? extends SmoothUnivariateDistribution>> learners) Creates a new instance of EMLearner
PDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions) Creates a new instance of ScalarMixtureDensityModel
PDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions, double[] priorWeights) Creates a new instance of ScalarMixtureDensityModel
ScalarMixtureDensityModel(java.util.Collection<? extends SmoothUnivariateDistribution> distributions) Creates a new instance of ScalarMixtureDensityModel
ScalarMixtureDensityModel(java.util.Collection<? extends SmoothUnivariateDistribution> distributions, double[] priorWeights) Creates a new instance of ScalarMixtureDensityModel

Uses of SmoothUnivariateDistribution in gov.sandia.cognition.statistics.method

Methods in gov.sandia.cognition.statistics.method that return SmoothUnivariateDistribution

Modifier and Type	Method and Description
static SmoothUnivariateDistribution	MaximumLikelihoodDistributionEstimator.estimateContinuousDistribution(java.util.Collection<java.lang.Double> data) Estimates a continuous distribution.

Methods in gov.sandia.cognition.statistics.method with parameters of type SmoothUnivariateDistribution

Modifier and Type	Method and Description
static InputOutputPair<java.lang.Double,java.lang.Double>	InverseTransformSampling.inverseNewtonsMethod(SmoothUnivariateDistribution distribution, double p, double tolerance) Inverts the given CDF, finding the value of "x" so that CDF(x)=p using a root-finding algorithm.