org.apache.commons.math3.distribution
Interface RealDistribution

All Known Implementing Classes:
AbstractRealDistribution, BetaDistribution, CauchyDistribution, ChiSquaredDistribution, EmpiricalDistribution, EnumeratedRealDistribution, ExponentialDistribution, FDistribution, GammaDistribution, LevyDistribution, LogNormalDistribution, NormalDistribution, TDistribution, TriangularDistribution, UniformRealDistribution, WeibullDistribution

public interface RealDistribution

Base interface for distributions on the reals.

Since:
3.0
Version:
$Id: RealDistribution.java 1416643 2012-12-03 19:37:14Z tn $

Method Summary
 double cumulativeProbability(double x)
          For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x).
 double cumulativeProbability(double x0, double x1)
          Deprecated. As of 3.1. In 4.0, this method will be renamed probability(double x0, double x1).
 double density(double x)
          Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
 double getNumericalMean()
          Use this method to get the numerical value of the mean of this distribution.
 double getNumericalVariance()
          Use this method to get the numerical value of the variance of this distribution.
 double getSupportLowerBound()
          Access the lower bound of the support.
 double getSupportUpperBound()
          Access the upper bound of the support.
 double inverseCumulativeProbability(double p)
          Computes the quantile function of this distribution.
 boolean isSupportConnected()
          Use this method to get information about whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support.
 boolean isSupportLowerBoundInclusive()
          Deprecated. to be removed in 4.0
 boolean isSupportUpperBoundInclusive()
          Deprecated. to be removed in 4.0
 double probability(double x)
          For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
 void reseedRandomGenerator(long seed)
          Reseed the random generator used to generate samples.
 double sample()
          Generate a random value sampled from this distribution.
 double[] sample(int sampleSize)
          Generate a random sample from the distribution.
 

Method Detail

probability

double probability(double x)
For a random variable X whose values are distributed according to this distribution, this method returns P(X = x). In other words, this method represents the probability mass function (PMF) for the distribution.

Parameters:
x - the point at which the PMF is evaluated
Returns:
the value of the probability mass function at point x

density

double density(double x)
Returns the probability density function (PDF) of this distribution evaluated at the specified point x. In general, the PDF is the derivative of the CDF. If the derivative does not exist at x, 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 - the point at which the PDF is evaluated
Returns:
the value of the probability density function at point x

cumulativeProbability

double cumulativeProbability(double x)
For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x). In other words, this method represents the (cumulative) distribution function (CDF) for this distribution.

Parameters:
x - the 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

cumulativeProbability

@Deprecated
double cumulativeProbability(double x0,
                                        double x1)
                             throws NumberIsTooLargeException
Deprecated. As of 3.1. In 4.0, this method will be renamed probability(double x0, double x1).

For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).

Parameters:
x0 - the exclusive lower bound
x1 - the inclusive upper bound
Returns:
the probability that a random variable with this distribution takes a value between x0 and x1, excluding the lower and including the upper endpoint
Throws:
NumberIsTooLargeException - if x0 > x1

inverseCumulativeProbability

double inverseCumulativeProbability(double p)
                                    throws OutOfRangeException
Computes the quantile function of this distribution. For a random variable X distributed according to this distribution, the returned value is

Parameters:
p - the cumulative probability
Returns:
the smallest p-quantile of this distribution (largest 0-quantile for p = 0)
Throws:
OutOfRangeException - if p < 0 or p > 1

getNumericalMean

double getNumericalMean()
Use this method to get the numerical value of the mean of this distribution.

Returns:
the mean or Double.NaN if it is not defined

getNumericalVariance

double getNumericalVariance()
Use this method to get the numerical value of the variance of this distribution.

Returns:
the variance (possibly Double.POSITIVE_INFINITY as for certain cases in TDistribution) or Double.NaN if it is not defined

getSupportLowerBound

double getSupportLowerBound()
Access the lower bound of the support. This method must return the same value as inverseCumulativeProbability(0). In other words, this method must return

inf {x in R | P(X <= x) > 0}.

Returns:
lower bound of the support (might be Double.NEGATIVE_INFINITY)

getSupportUpperBound

double getSupportUpperBound()
Access the upper bound of the support. This method must return the same value as inverseCumulativeProbability(1). In other words, this method must return

inf {x in R | P(X <= x) = 1}.

Returns:
upper bound of the support (might be Double.POSITIVE_INFINITY)

isSupportLowerBoundInclusive

boolean isSupportLowerBoundInclusive()
Deprecated. to be removed in 4.0

Whether or not the lower bound of support is in the domain of the density function. Returns true iff getSupporLowerBound() is finite and density(getSupportLowerBound()) returns a non-NaN, non-infinite value.

Returns:
true if the lower bound of support is finite and the density function returns a non-NaN, non-infinite value there

isSupportUpperBoundInclusive

boolean isSupportUpperBoundInclusive()
Deprecated. to be removed in 4.0

Whether or not the upper bound of support is in the domain of the density function. Returns true iff getSupportUpperBound() is finite and density(getSupportUpperBound()) returns a non-NaN, non-infinite value.

Returns:
true if the upper bound of support is finite and the density function returns a non-NaN, non-infinite value there

isSupportConnected

boolean isSupportConnected()
Use this method to get information about 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 or not

reseedRandomGenerator

void reseedRandomGenerator(long seed)
Reseed the random generator used to generate samples.

Parameters:
seed - the new seed

sample

double sample()
Generate a random value sampled from this distribution.

Returns:
a random value.

sample

double[] sample(int sampleSize)
Generate a random sample from the distribution.

Parameters:
sampleSize - the number of random values to generate
Returns:
an array representing the random sample
Throws:
NotStrictlyPositiveException - if sampleSize is not positive


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