Class UniformContinuousDistribution
- java.lang.Object
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- org.apache.commons.statistics.distribution.UniformContinuousDistribution
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- All Implemented Interfaces:
ContinuousDistribution
public class UniformContinuousDistribution extends java.lang.ObjectImplementation of the uniform 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 UniformContinuousDistribution(double lower, double upper)Creates a uniform 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.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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Constructor Detail
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UniformContinuousDistribution
public UniformContinuousDistribution(double lower, double upper)Creates a uniform distribution.- Parameters:
lower- Lower bound of this distribution (inclusive).upper- Upper bound of this distribution (exclusive).- Throws:
java.lang.IllegalArgumentException- iflower >= upper.
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Method Detail
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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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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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getMean
public double getMean()
Gets the mean of this distribution. For lower boundlowerand upper boundupper, the mean is0.5 * (lower + upper).- Returns:
- the mean, or
Double.NaNif it is not defined.
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getVariance
public double getVariance()
Gets the variance of this distribution. For lower boundlowerand upper boundupper, the variance is(upper - lower)^2 / 12.- 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}. The lower bound of the support is equal to the lower bound parameter of the distribution.- Returns:
- 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}. The upper bound of the support is equal to the upper bound parameter of the distribution.- Returns:
- 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. The support of this distribution is connected.- Returns:
true
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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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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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