Package | Description |
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gov.sandia.cognition.statistics.bayesian |
Provides algorithms for computing Bayesian estimates of parameters.
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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.
|
Modifier and Type | Method and Description |
---|---|
StudentTDistribution |
BayesianRobustLinearRegression.PredictiveDistribution.evaluate(Vectorizable input) |
Modifier and Type | Method and Description |
---|---|
StudentTDistribution |
UnivariateGaussianMeanVarianceBayesianEstimator.createPredictiveDistribution(NormalInverseGammaDistribution posterior) |
Modifier and Type | Class and Description |
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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
|
Modifier and Type | Method and Description |
---|---|
StudentTDistribution |
StudentTDistribution.clone() |
StudentTDistribution |
StudentTDistribution.MaximumLikelihoodEstimator.learn(java.util.Collection<? extends java.lang.Double> data)
Creates a new instance of UnivariateGaussian from the given data
|
Constructor and Description |
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CDF(StudentTDistribution other)
Creates a new instance of CDF
|
PDF(StudentTDistribution other)
Creates a new instance of PDF
|
StudentTDistribution(StudentTDistribution other)
Copy constructor
|