Package org.apache.commons.math4.distribution

Class AbstractRealDistribution

  • All Implemented Interfaces:
    java.io.Serializable, RealDistribution, ContinuousDistribution
    Direct Known Subclasses:
    EmpiricalDistribution
    public abstract class AbstractRealDistribution
extends java.lang.Object
implements RealDistribution, java.io.Serializable
    Base class for probability distributions on the reals. Default implementations are provided for some of the methods that do not vary from distribution to distribution.

    This base class provides a default factory method for creating a sampler instance that uses the inversion method for generating random samples that follow the distribution.

    Since:
    3.0
    See Also:
    Serialized Form

    • Field Detail

      • SOLVER_DEFAULT_ABSOLUTE_ACCURACY

        public static final double SOLVER_DEFAULT_ABSOLUTE_ACCURACY
        Default absolute accuracy for inverse cumulative computation.
        See Also:
        Constant Field Values

    • Constructor Detail

      • AbstractRealDistribution

        public AbstractRealDistribution()

    • Method Detail

      • probability

        public double 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).
        Specified by:
        probability in interface ContinuousDistribution
        Parameters:
        x0 - Lower bound (excluded).
        x1 - Upper bound (included).
        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. The default implementation uses the identity P(x0 < X <= x1) = P(X <= x1) - P(X <= x0)
        Since:
        3.1

      • 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.
        Returns:
        the maximum absolute error in inverse cumulative probability estimates

      • probability

        public 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.
        Specified by:
        probability in interface ContinuousDistribution
        Parameters:
        x - Point at which the PMF is evaluated.
        Returns:
        zero.
        Since:
        3.1

      • logDensity

        public double logDensity​(double x)
        Returns the natural logarithm of the probability density function (PDF) of this distribution evaluated at the specified point x.

        The default implementation simply computes the logarithm of density(x).

        Specified by:
        logDensity in interface ContinuousDistribution
        Parameters:
        x - Point at which the PDF is evaluated.
        Returns:
        the logarithm of the value of the probability density function at x.

      • sample

        public static double[] sample​(int n,
                              ContinuousDistribution.Sampler sampler)
        Utility function for allocating an array and filling it with n samples generated by the given sampler.
        Parameters:
        n - Number of samples.
        sampler - Sampler.
        Returns:
        an array of size n.