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## org.apache.commons.math3.distribution
Class UniformRealDistribution

    java.lang.Object
      org.apache.commons.math3.distribution.AbstractRealDistribution
          org.apache.commons.math3.distribution.UniformRealDistribution

All Implemented Interfaces:
  Serializable, RealDistribution

    public class UniformRealDistribution

extends AbstractRealDistribution

Implementation of the uniform real distribution.

Since:
  3.0
Version:
  $Id: UniformRealDistribution.java 1416643 2012-12-03 19:37:14Z tn $
See Also:
  Uniform distribution (continuous), at Wikipedia, Serialized Form

Field Summary
`static double` | `DEFAULT_INVERSE_ABSOLUTE_ACCURACY` Default inverse cumulative probability accuracy.

Fields inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution
`random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY`

Constructor Summary
`UniformRealDistribution()` Create a standard uniform real distribution with lower bound (inclusive) equal to zero and upper bound (exclusive) equal to one.
`UniformRealDistribution(double lower, double upper)` Create a uniform real distribution using the given lower and upper bounds.
`UniformRealDistribution(double lower, double upper, double inverseCumAccuracy)` Create a uniform distribution.
`UniformRealDistribution(RandomGenerator rng, double lower, double upper, double inverseCumAccuracy)` Creates a uniform distribution.

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` | `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.
`protected double` | `getSolverAbsoluteAccuracy()` Returns the solver absolute accuracy for inverse cumulative computation.
`double` | `getSupportLowerBound()` Access the lower bound of the support.
`double` | `getSupportUpperBound()` Access the upper bound of the support.
`boolean` | `isSupportConnected()` Use this method to get information about whether the support is connected, i.e.
`boolean` | `isSupportLowerBoundInclusive()` Whether or not the lower bound of support is in the domain of the density function.
`boolean` | `isSupportUpperBoundInclusive()` Whether or not the upper bound of support is in the domain of the density function.
`double` | `sample()` Generate a random value sampled from this distribution.

Methods inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution
`cumulativeProbability, inverseCumulativeProbability, probability, probability, reseedRandomGenerator, sample`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Field Detail

### DEFAULT_INVERSE_ABSOLUTE_ACCURACY

    public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY

  Default inverse cumulative probability accuracy.

  See Also:
    Constant Field Values

Constructor Detail

### UniformRealDistribution

    public UniformRealDistribution()

  Create a standard uniform real distribution with lower bound (inclusive) equal to zero and upper bound (exclusive) equal to one.

### UniformRealDistribution

    public UniformRealDistribution(double lower,
                                   double upper)
                            throws NumberIsTooLargeException

  Create a uniform real distribution using the given lower and upper bounds.

  Parameters:
    `lower` - Lower bound of this distribution (inclusive).
    `upper` - Upper bound of this distribution (exclusive).
  Throws:
    `NumberIsTooLargeException` - if `lower >= upper`.

### UniformRealDistribution

    public UniformRealDistribution(double lower,
                                   double upper,
                                   double inverseCumAccuracy)
                            throws NumberIsTooLargeException

  Create a uniform distribution.

  Parameters:
    `lower` - Lower bound of this distribution (inclusive).
    `upper` - Upper bound of this distribution (exclusive).
    `inverseCumAccuracy` - Inverse cumulative probability accuracy.
  Throws:
    `NumberIsTooLargeException` - if `lower >= upper`.

### UniformRealDistribution

    public UniformRealDistribution(RandomGenerator rng,
                                   double lower,
                                   double upper,
                                   double inverseCumAccuracy)
                            throws NumberIsTooLargeException

  Creates a uniform distribution.

  Parameters:
    `rng` - Random number generator.
    `lower` - Lower bound of this distribution (inclusive).
    `upper` - Upper bound of this distribution (exclusive).
    `inverseCumAccuracy` - Inverse cumulative probability accuracy.
  Throws:
    `NumberIsTooLargeException` - if `lower >= upper`.
  Since:
    3.1

Method Detail

### density

    public 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

    public 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`

### getSolverAbsoluteAccuracy

    protected double getSolverAbsoluteAccuracy()

  Returns the solver absolute accuracy for inverse cumulative computation. You can override this method in order to use a Brent solver with an absolute accuracy different from the default.

  Overrides:
    `getSolverAbsoluteAccuracy` in class `AbstractRealDistribution`
  Returns:
    the maximum absolute error in inverse cumulative probability estimates

### getNumericalMean

    public double getNumericalMean()

  Use this method to get the numerical value of the mean of this distribution. For lower bound `lower` and upper bound `upper`, the mean is `0.5 * (lower + upper)`.

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

### getNumericalVariance

    public double getNumericalVariance()

  Use this method to get the numerical value of the variance of this distribution. For lower bound `lower` and upper bound `upper`, the variance is `(upper - lower)^2 / 12`.

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

### getSupportLowerBound

    public 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}`.

  The lower bound of the support is equal to the lower bound parameter of the distribution.

  Returns:
    lower bound of the support

### getSupportUpperBound

    public 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}`.

  The upper bound of the support is equal to the upper bound parameter of the distribution.

  Returns:
    upper bound of the support

### isSupportLowerBoundInclusive

    public boolean isSupportLowerBoundInclusive()

  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

    public boolean isSupportUpperBoundInclusive()

  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

    public 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. The support of this distribution is connected.

  Returns:
    `true`

### sample

    public double sample()

  Generate a random value sampled from this distribution. The default implementation uses the inversion method.

  Specified by:
    `sample` in interface `RealDistribution`
  Overrides:
    `sample` in class `AbstractRealDistribution`
  Returns:
    a random value.

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