Class CauchyDistribution
- java.lang.Object
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- org.apache.commons.statistics.distribution.CauchyDistribution
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- All Implemented Interfaces:
ContinuousDistribution
public class CauchyDistribution extends java.lang.ObjectImplementation of the Cauchy 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 CauchyDistribution(double median, double scale)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.doublegetMedian()Access the median.doublegetScale()Access the scale parameter.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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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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getMedian
public double getMedian()
Access the median.- Returns:
- the median for this distribution.
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getScale
public double getScale()
Access the scale parameter.- Returns:
- the scale parameter for this distribution.
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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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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.
Double.NEGATIVE_INFINITYwhenp == 0andDouble.POSITIVE_INFINITYwhenp == 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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getMean
public double getMean()
Gets the mean of this distribution. The mean is always undefined no matter the parameters.- Returns:
- mean (always Double.NaN)
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getVariance
public double getVariance()
Gets the variance of this distribution. The variance is always undefined no matter the parameters.- Returns:
- variance (always Double.NaN)
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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}. The lower bound of the support is always negative infinity no matter the parameters.- Returns:
- lower bound of the support (always Double.NEGATIVE_INFINITY)
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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}. The upper bound of the support is always positive infinity no matter the parameters.- Returns:
- upper bound of the support (always Double.POSITIVE_INFINITY)
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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. The support of this distribution is connected.- Returns:
true
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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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