Package | Description |
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gov.sandia.cognition.statistics |
Provides the inheritance hierarchy for general statistical methods and distributions.
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gov.sandia.cognition.statistics.distribution |
Provides statistical distributions.
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gov.sandia.cognition.statistics.method |
Provides algorithms for evaluating statistical data and conducting statistical inference, particularly frequentist methods.
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gov.sandia.cognition.statistics.montecarlo |
Provides Monte Carlo procedures for numerical integration and sampling.
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Modifier and Type | Interface and Description |
---|---|
interface |
UnivariateProbabilityDensityFunction
A PDF that takes doubles as input.
|
Modifier and Type | Method and Description |
---|---|
ProbabilityDensityFunction<DataType> |
ProbabilityDensityFunction.getProbabilityFunction() |
Modifier and Type | Class and Description |
---|---|
static class |
BetaDistribution.PDF
Beta distribution probability density function
|
static class |
CauchyDistribution.PDF
PDF of the CauchyDistribution.
|
static class |
ChiSquareDistribution.PDF
PDF of the Chi-Square distribution
|
static class |
DirichletDistribution.PDF
PDF of the Dirichlet distribution.
|
static class |
ExponentialDistribution.PDF
PDF of the ExponentialDistribution.
|
static class |
GammaDistribution.PDF
Closed-form PDF of the Gamma distribution
|
static class |
InverseGammaDistribution.PDF
PDF of the inverseRootFinder-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...
|
static class |
LaplaceDistribution.PDF
The PDF of a Laplace Distribution.
|
static class |
LogisticDistribution.PDF
PDF of the LogisticDistribution
|
static class |
LogNormalDistribution.PDF
PDF of a Log-normal distribution
|
static class |
MixtureOfGaussians.PDF
PDF of the MixtureOfGaussians
|
static class |
MultivariateGaussian.PDF
PDF of a multivariate Gaussian
|
static class |
MultivariateMixtureDensityModel.PDF<DistributionType extends ClosedFormComputableDistribution<Vector>>
PDF of the MultivariateMixtureDensityModel
|
static class |
MultivariateStudentTDistribution.PDF
PDF of the MultivariateStudentTDistribution
|
static class |
NormalInverseGammaDistribution.PDF
PDF of the NormalInverseGammaDistribution
|
static class |
NormalInverseWishartDistribution.PDF
PDF of the normal inverse-Wishart distribution.
|
static class |
ParetoDistribution.PDF
PDF of the ParetoDistribution
|
static class |
ScalarMixtureDensityModel.PDF
PDF of the SMDM
|
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
|
static class |
UniformDistribution.PDF
Probability density function of a Uniform Distribution
|
static class |
UnivariateGaussian.PDF
PDF of the underlying Gaussian.
|
static class |
WeibullDistribution.PDF
PDF of the Weibull distribution
|
Modifier and Type | Method and Description |
---|---|
static <ValueType> |
ImportanceSampling.sample(ProbabilityDensityFunction<ValueType> importanceDistribution,
Evaluator<ValueType,java.lang.Double> targetDistribution,
java.util.Random random,
int numSamples)
Importance sampling is a technique for estimating properties of
a target distribution, while only having samples generated from an
"importance" distribution rather than the target distribution.
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Constructor and Description |
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ImportanceSampler(ProbabilityDensityFunction<DataType> importanceDistribution)
Creates a new instance of ImportanceSampler.
|