Class NakagamiDistribution
- java.lang.Object
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- org.apache.commons.statistics.distribution.NakagamiDistribution
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- All Implemented Interfaces:
ContinuousDistribution
public class NakagamiDistribution extends java.lang.ObjectThis class implements the Nakagami distribution.
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Nested Class Summary
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Nested classes/interfaces inherited from interface org.apache.commons.statistics.distribution.ContinuousDistribution
ContinuousDistribution.Sampler
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Constructor Summary
Constructors Constructor Description NakagamiDistribution(double mu, double omega)Creates a distribution.
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Method Summary
Modifier and Type Method Description ContinuousDistribution.SamplercreateSampler(UniformRandomProvider rng)Creates a sampler.doublecumulativeProbability(double x)For a random variableXwhose values are distributed according to this distribution, this method returnsP(X <= x).doubledensity(double x)Returns the probability density function (PDF) of this distribution evaluated at the specified pointx.doublegetMean()Gets the mean of this distribution.doublegetScale()Access the scale parameter,omega.doublegetShape()Access the shape parameter,mu.doublegetSupportLowerBound()Gets the lower bound of the support.doublegetSupportUpperBound()Gets the upper bound of the support.doublegetVariance()Gets the variance of this distribution.doubleinverseCumulativeProbability(double p)Computes the quantile function of this distribution.booleanisSupportConnected()Indicates whether the support is connected, i.e.static double[]sample(int n, ContinuousDistribution.Sampler sampler)Utility function for allocating an array and filling it withnsamples generated by the givensampler.-
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface org.apache.commons.statistics.distribution.ContinuousDistribution
logDensity, probability, probability
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Method Detail
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getShape
public double getShape()
Access the shape parameter,mu.- Returns:
- the shape parameter.
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getScale
public double getScale()
Access the scale parameter,omega.- Returns:
- the scale parameter.
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density
public double density(double x)
Returns the probability density function (PDF) of this distribution evaluated at the specified pointx. In general, the PDF is the derivative of theCDF. If the derivative does not exist atx, then an appropriate replacement should be returned, e.g.Double.POSITIVE_INFINITY,Double.NaN, or the limit inferior or limit superior of the difference quotient.- Parameters:
x- Point at which the PDF is evaluated.- Returns:
- the value of the probability density function at
x.
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cumulativeProbability
public double cumulativeProbability(double x)
For a random variableXwhose values are distributed according to this distribution, this method returnsP(X <= x). In other words, this method represents the (cumulative) distribution function (CDF) for this distribution.- Parameters:
x- Point at which the CDF is evaluated.- Returns:
- the probability that a random variable with this
distribution takes a value less than or equal to
x.
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getMean
public double getMean()
Gets the mean of this distribution.- Returns:
- the mean, or
Double.NaNif it is not defined.
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getVariance
public double getVariance()
Gets the variance of this distribution.- Returns:
- the variance, or
Double.NaNif it is not defined.
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getSupportLowerBound
public double getSupportLowerBound()
Gets the lower bound of the support. It must return the same value asinverseCumulativeProbability(0), i.e.inf {x in R | P(X <= x) > 0}.- Returns:
- the lower bound of the support.
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getSupportUpperBound
public double getSupportUpperBound()
Gets the upper bound of the support. It must return the same value asinverseCumulativeProbability(1), i.e.inf {x in R | P(X <= x) = 1}.- Returns:
- the upper bound of the support.
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isSupportConnected
public boolean isSupportConnected()
Indicates whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support.- Returns:
- whether the support is connected.
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inverseCumulativeProbability
public double inverseCumulativeProbability(double p)
Computes the quantile function of this distribution. For a random variableXdistributed according to this distribution, the returned value isinf{x in R | P(X<=x) >= p}for0 < p <= 1,inf{x in R | P(X<=x) > 0}forp = 0.
ContinuousDistribution.getSupportLowerBound()forp = 0,ContinuousDistribution.getSupportUpperBound()forp = 1.
- Specified by:
inverseCumulativeProbabilityin interfaceContinuousDistribution- Parameters:
p- Cumulative probability.- Returns:
- the smallest
p-quantile of this distribution (largest 0-quantile forp = 0).
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sample
public static double[] sample(int n, ContinuousDistribution.Sampler sampler)Utility function for allocating an array and filling it withnsamples generated by the givensampler.- Parameters:
n- Number of samples.sampler- Sampler.- Returns:
- an array of size
n.
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createSampler
public ContinuousDistribution.Sampler createSampler(UniformRandomProvider rng)
Creates a sampler.- Specified by:
createSamplerin interfaceContinuousDistribution- Parameters:
rng- Generator of uniformly distributed numbers.- Returns:
- a sampler that produces random numbers according this distribution.
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