public static class ScalarMixtureDensityModel.PDF extends ScalarMixtureDensityModel implements UnivariateProbabilityDensityFunction
ScalarMixtureDensityModel.CDF, ScalarMixtureDensityModel.EMLearner, ScalarMixtureDensityModel.PDF
distributions, priorWeights
Constructor and Description |
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PDF()
Creates a new instance of ScalarMixtureDensityModel
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PDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions)
Creates a new instance of ScalarMixtureDensityModel
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PDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions,
double[] priorWeights)
Creates a new instance of ScalarMixtureDensityModel
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PDF(ScalarMixtureDensityModel other)
Copy constructor
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PDF(SmoothUnivariateDistribution... distributions)
Creates a new instance of ScalarMixtureDensityModel
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Modifier and Type | Method and Description |
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double |
evaluate(double input)
Produces a double output for the given double input
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java.lang.Double |
evaluate(java.lang.Double input)
Evaluates the function on the given input and returns the output.
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double |
evaluateAsDouble(java.lang.Double input)
Evaluates the scalar function as a double.
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ScalarMixtureDensityModel.PDF |
getProbabilityFunction()
Gets the distribution function associated with this Distribution,
either the PDF or PMF.
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double |
logEvaluate(double input)
Evaluate the natural logarithm of the distribution function.
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double |
logEvaluate(java.lang.Double input)
Evaluate the natural logarithm of the distribution function.
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clone, convertFromVector, convertToVector, getCDF, getMaxSupport, getMean, getMeanAsDouble, getMinSupport, getVariance, sampleAsDouble, sampleAsDoubles, sampleInto
getDistributionCount, getDistributions, getPriorWeights, getPriorWeightSum, sample, sampleInto, setDistributions, setPriorWeights, toString
sample
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
getCDF, getMean, sampleAsDouble, sampleAsDoubles, sampleInto
getMaxSupport, getMeanAsDouble, getMinSupport, getVariance
sample, sample, sampleInto
clone, convertFromVector, convertToVector
public PDF()
public PDF(SmoothUnivariateDistribution... distributions)
distributions
- Distributions that comprise the SMDM with equal prior weightpublic PDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions)
distributions
- Distributions that comprise the SMDM with equal prior weightpublic PDF(java.util.Collection<? extends SmoothUnivariateDistribution> distributions, double[] priorWeights)
distributions
- Distributions that comprise the SMDMpriorWeights
- Weights proportionate by which the distributions are sampledpublic PDF(ScalarMixtureDensityModel other)
other
- SMDM to copypublic double logEvaluate(java.lang.Double input)
ProbabilityFunction
logEvaluate
in interface ProbabilityFunction<java.lang.Double>
input
- The input to be evaluatedpublic java.lang.Double evaluate(java.lang.Double input)
Evaluator
evaluate
in interface Evaluator<java.lang.Double,java.lang.Double>
evaluate
in interface ScalarFunction<java.lang.Double>
evaluate
in interface UnivariateScalarFunction
input
- The input to evaluate.public double evaluateAsDouble(java.lang.Double input)
ScalarFunction
evaluateAsDouble
in interface ScalarFunction<java.lang.Double>
evaluateAsDouble
in interface UnivariateScalarFunction
input
- The input value.public double evaluate(double input)
UnivariateScalarFunction
evaluate
in interface UnivariateScalarFunction
input
- Input to the Evaluatorpublic ScalarMixtureDensityModel.PDF getProbabilityFunction()
ComputableDistribution
getProbabilityFunction
in interface ComputableDistribution<java.lang.Double>
getProbabilityFunction
in interface ProbabilityDensityFunction<java.lang.Double>
getProbabilityFunction
in interface SmoothUnivariateDistribution
getProbabilityFunction
in interface UnivariateProbabilityDensityFunction
getProbabilityFunction
in class ScalarMixtureDensityModel
public double logEvaluate(double input)
UnivariateProbabilityDensityFunction
logEvaluate
in interface UnivariateProbabilityDensityFunction
input
- The input value.