public static class BetaDistribution.CDF extends BetaDistribution implements SmoothCumulativeDistributionFunction
BetaDistribution.CDF, BetaDistribution.MomentMatchingEstimator, BetaDistribution.PDF, BetaDistribution.WeightedMomentMatchingEstimator
DEFAULT_ALPHA, DEFAULT_BETA
Constructor and Description |
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CDF()
Default constructor.
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CDF(BetaDistribution other)
Copy constructor
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CDF(double alpha,
double beta)
Creates a new CDF
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Modifier and Type | Method and Description |
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java.lang.Double |
differentiate(java.lang.Double input)
Differentiates the output with respect to the input
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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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static double |
evaluate(double x,
double alpha,
double beta)
Evaluate the Beta-distribution CDF for Beta(x;alpha,beta)
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double |
evaluateAsDouble(java.lang.Double input)
Evaluates the scalar function as a double.
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BetaDistribution.CDF |
getCDF()
Gets the CDF of a scalar distribution.
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BetaDistribution.PDF |
getDerivative()
Gets the closed-form derivative of the function.
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clone, convertFromVector, convertToVector, getAlpha, getBeta, getEstimator, getMaxSupport, getMeanAsDouble, getMinSupport, getProbabilityFunction, getVariance, sampleAsDouble, sampleInto, setAlpha, setBeta
getMean, sampleAsDoubles, sampleInto
sample, sample
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getMean, getProbabilityFunction, sampleAsDouble, sampleAsDoubles, sampleInto
getMaxSupport, getMeanAsDouble, getMinSupport, getVariance
sample, sample, sampleInto
clone, convertFromVector, convertToVector
public CDF()
public CDF(double alpha, double beta)
alpha
- Alpha shape parameter, must be greater than 0 (typically greater than 1)beta
- Beta shape parameter, must be greater than 0 (typically greater than 1)public CDF(BetaDistribution other)
other
- Underlying Beta Distributionpublic 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 static double evaluate(double x, double alpha, double beta)
x
- Input to the beta CDF, must be on the interval [0,1]alpha
- Alpha shape parameter, must be greater than 0 (typically greater than 1)beta
- Beta shape parameter, must be greater than 0 (typically greater than 1)public BetaDistribution.CDF getCDF()
UnivariateDistribution
getCDF
in interface ClosedFormUnivariateDistribution<java.lang.Double>
getCDF
in interface SmoothUnivariateDistribution
getCDF
in interface UnivariateDistribution<java.lang.Double>
getCDF
in class BetaDistribution
public BetaDistribution.PDF getDerivative()
ClosedFormDifferentiableEvaluator
getDerivative
in interface ClosedFormDifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>
getDerivative
in interface SmoothCumulativeDistributionFunction
public java.lang.Double differentiate(java.lang.Double input)
DifferentiableEvaluator
differentiate
in interface DifferentiableEvaluator<java.lang.Double,java.lang.Double,java.lang.Double>
input
- Input about which to compute the derivative