Package org.apache.commons.math.distribution

Class AbstractIntegerDistribution

    • Field Summary

      Fields 
      Modifier and Type Field Description
      protected RandomDataImpl randomData
      RandomData instance used to generate samples from the distribution

    • Method Summary

      All Methods Instance Methods Abstract Methods Concrete Methods 
      Modifier and Type Method Description
      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)
      For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
      abstract double cumulativeProbability​(int x)
      For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
      double cumulativeProbability​(int x0, int x1)
      For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
      protected abstract int getDomainLowerBound​(double p)
      Access the domain value lower bound, based on p, used to bracket a PDF root.
      protected abstract int getDomainUpperBound​(double p)
      Access the domain value upper bound, based on p, used to bracket a PDF root.
      int inverseCumulativeProbability​(double p)
      For a random variable X whose values are distributed according to this distribution, this method returns the largest x, such that P(X ≤ x) ≤ p.
      boolean isSupportLowerBoundInclusive()
      Use this method to get information about whether the lower bound of the support is inclusive or not.
      boolean isSupportUpperBoundInclusive()
      Use this method to get information about whether the upper bound of the support is inclusive or not.
      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)
      Reseeds the random generator used to generate samples.
      int sample()
      Generates a random value sampled from this distribution.
      int[] sample​(int sampleSize)
      Generates a random sample from the distribution.

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Field Detail

      • randomData

        protected final RandomDataImpl randomData
        RandomData instance used to generate samples from the distribution
        Since:
        2.2

    • Constructor Detail

      • AbstractIntegerDistribution

        protected AbstractIntegerDistribution()
        Default constructor.

    • Method Detail

      • cumulativeProbability

        public double cumulativeProbability​(double x)
                             throws MathException
        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, or CDF, for this distribution.

        If x does not represent an integer value, the CDF is evaluated at the greatest integer less than x.

        Specified by:
        cumulativeProbability in interface Distribution
        Parameters:
        x - the value at which the distribution function is evaluated.
        Returns:
        cumulative probability that a random variable with this distribution takes a value less than or equal to x
        Throws:
        MathException - if the cumulative probability can not be computed due to convergence or other numerical errors.

      • cumulativeProbability

        public double cumulativeProbability​(double x0,
                                    double x1)
                             throws MathException
        For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
        Specified by:
        cumulativeProbability in interface Distribution
        Overrides:
        cumulativeProbability in class AbstractDistribution
        Parameters:
        x0 - the (inclusive) lower bound
        x1 - the (inclusive) upper bound
        Returns:
        the probability that a random variable with this distribution will take a value between x0 and x1, including the endpoints.
        Throws:
        MathException - if the cumulative probability can not be computed due to convergence or other numerical errors.
        java.lang.IllegalArgumentException - if x0 > x1

      • cumulativeProbability

        public abstract double cumulativeProbability​(int x)
                                      throws MathException
        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 distribution function, or PDF, for this distribution.
        Specified by:
        cumulativeProbability in interface IntegerDistribution
        Parameters:
        x - the value at which the PDF is evaluated.
        Returns:
        PDF for this distribution.
        Throws:
        MathException - if the cumulative probability can not be computed due to convergence or other numerical errors.

      • 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, or PMF, for the distribution.

        If x does not represent an integer value, 0 is returned.

        Specified by:
        probability in interface DiscreteDistribution
        Parameters:
        x - the value at which the probability density function is evaluated
        Returns:
        the value of the probability density function at x

      • cumulativeProbability

        public double cumulativeProbability​(int x0,
                                    int x1)
                             throws MathException
        For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
        Specified by:
        cumulativeProbability in interface IntegerDistribution
        Parameters:
        x0 - the inclusive, lower bound
        x1 - the inclusive, upper bound
        Returns:
        the cumulative probability.
        Throws:
        MathException - if the cumulative probability can not be computed due to convergence or other numerical errors.
        java.lang.IllegalArgumentException - if x0 > x1

      • inverseCumulativeProbability

        public int inverseCumulativeProbability​(double p)
                                 throws MathException
        For a random variable X whose values are distributed according to this distribution, this method returns the largest x, such that P(X ≤ x) ≤ p.
        Specified by:
        inverseCumulativeProbability in interface IntegerDistribution
        Parameters:
        p - the desired probability
        Returns:
        the largest x such that P(X ≤ x) <= p
        Throws:
        MathException - if the inverse cumulative probability can not be computed due to convergence or other numerical errors.
        java.lang.IllegalArgumentException - if p < 0 or p > 1

      • reseedRandomGenerator

        public void reseedRandomGenerator​(long seed)
        Reseeds the random generator used to generate samples.
        Parameters:
        seed - the new seed
        Since:
        2.2

      • sample

        public int sample()
           throws MathException
        Generates a random value sampled from this distribution. The default implementation uses the inversion method.
        Returns:
        random value
        Throws:
        MathException - if an error occurs generating the random value
        Since:
        2.2

      • sample

        public int[] sample​(int sampleSize)
             throws MathException
        Generates a random sample from the distribution. The default implementation generates the sample by calling sample() in a loop.
        Parameters:
        sampleSize - number of random values to generate
        Returns:
        an array representing the random sample
        Throws:
        MathException - if an error occurs generating the sample
        java.lang.IllegalArgumentException - if sampleSize is not positive
        Since:
        2.2

      • getDomainLowerBound

        protected abstract int getDomainLowerBound​(double p)
        Access the domain value lower bound, based on p, used to bracket a PDF root. This method is used by inverseCumulativeProbability(double) to find critical values.
        Parameters:
        p - the desired probability for the critical value
        Returns:
        domain value lower bound, i.e. P(X < lower bound) < p

      • getDomainUpperBound

        protected abstract int getDomainUpperBound​(double p)
        Access the domain value upper bound, based on p, used to bracket a PDF root. This method is used by inverseCumulativeProbability(double) to find critical values.
        Parameters:
        p - the desired probability for the critical value
        Returns:
        domain value upper bound, i.e. P(X < upper bound) > p

      • isSupportLowerBoundInclusive

        public boolean isSupportLowerBoundInclusive()
        Use this method to get information about whether the lower bound of the support is inclusive or not. For discrete support, only true here is meaningful.
        Returns:
        true (always but at Integer.MIN_VALUE because of the nature of discrete support)
        Since:
        2.2

      • isSupportUpperBoundInclusive

        public boolean isSupportUpperBoundInclusive()
        Use this method to get information about whether the upper bound of the support is inclusive or not. For discrete support, only true here is meaningful.
        Returns:
        true (always but at Integer.MAX_VALUE because of the nature of discrete support)
        Since:
        2.2