public static class MultivariatePolyaDistribution.PMF extends MultivariatePolyaDistribution implements ProbabilityMassFunction<Vector>, VectorInputEvaluator<Vector,java.lang.Double>
MultivariatePolyaDistribution.PMF
DEFAULT_DIMENSIONALITY, DEFAULT_NUM_TRIALS, parameters
Constructor and Description |
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PMF()
Creates a new instance of DirichletDistribution
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PMF(int dimensionality,
int numTrials)
Creates a new instance of MultivariatePolyaDistribution
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PMF(MultivariatePolyaDistribution other)
Copy Constructor.
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PMF(Vector parameters,
int numTrials)
Creates a new instance of MultivariatePolyaDistribution
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Modifier and Type | Method and Description |
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java.lang.Double |
evaluate(Vector input)
Evaluates the function on the given input and returns the output.
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double |
getEntropy()
Gets the entropy of the values in the histogram.
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MultivariatePolyaDistribution.PMF |
getProbabilityFunction()
Gets the distribution function associated with this Distribution,
either the PDF or PMF.
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double |
logEvaluate(Vector input)
Evaluate the natural logarithm of the distribution function.
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clone, convertFromVector, convertToVector, getDomain, getDomainSize, getInputDimensionality, getMean, getNumTrials, getParameters, sampleInto, setNumTrials, setParameters, toString
sample, sample
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
getDomain, getDomainSize
sample, sample, sampleInto
clone
getInputDimensionality
public PMF()
public PMF(int dimensionality, int numTrials)
dimensionality
- Dimensionality of the distributionnumTrials
- Number of trials in the distribution, must be greater than 0.public PMF(Vector parameters, int numTrials)
parameters
- Parameters of the Dirichlet distribution, must be at least 2-dimensional
and each element must be positive.numTrials
- Number of trials in the distribution, must be greater than 0.public PMF(MultivariatePolyaDistribution other)
other
- MultivariatePolyaDistribution to copy.public MultivariatePolyaDistribution.PMF getProbabilityFunction()
ComputableDistribution
getProbabilityFunction
in interface ComputableDistribution<Vector>
getProbabilityFunction
in interface DiscreteDistribution<Vector>
getProbabilityFunction
in interface ProbabilityMassFunction<Vector>
getProbabilityFunction
in class MultivariatePolyaDistribution
public double logEvaluate(Vector input)
ProbabilityFunction
logEvaluate
in interface ProbabilityFunction<Vector>
input
- The input to be evaluatedpublic java.lang.Double evaluate(Vector input)
Evaluator
public double getEntropy()
ProbabilityMassFunction
getEntropy
in interface ProbabilityMassFunction<Vector>