Documentation of 'umontreal.iro.lecuyer.probdist.PoissonDist' Java class
PoissonDist
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umontreal.iro.lecuyer.probdist

Class PoissonDist

  • All Implemented Interfaces:
    Distribution

    public class PoissonDist
extends DiscreteDistributionInt
    Extends the class DiscreteDistributionInt for the Poisson distribution with mean λ >=  0. The mass function is

    p(x) = e-λλx/(x!),        for x = 0, 1,...

    and the distribution function is

    F(x) = e-λ∑j=0x  λj/(j!),        for x = 0, 1,....

    If one has to compute p(x) and/or F(x) for several values of x with the same λ, where λ is not too large, then it is more efficient to instantiate an object and use the non-static methods, since the functions will then be computed once and kept in arrays.

    For the static methods that compute F(x) and bar(F)(x), we exploit the relationship F(x) = 1 - Gx+1(λ), where Gx+1 is the gamma distribution function with parameters (α, λ) = (x + 1, 1).

    • Constructor Summary

      Constructors 
      Constructor and Description
      PoissonDist(double lambda)
      Creates an object that contains the probability and distribution functions, for the Poisson distribution with parameter lambda, which are computed and stored in dynamic arrays inside that object.

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method and Description
      static double barF(double lambda, int x)
      Computes and returns the value of the complementary Poisson distribution function, for λ = lambda.
      double barF(int x)
      Returns bar(F)(x), the complementary distribution function.
      static double cdf(double lambda, int x)
      Computes and returns the value of the Poisson distribution function F(x) for λ = lambda.
      double cdf(int x)
      Returns the distribution function F evaluated at x (see).
      static PoissonDist getInstanceFromMLE(int[] x, int n)
      Creates a new instance of a Poisson distribution with parameter λ estimated using the maximum likelihood method based on the n observations x[i], i = 0, 1,…, n - 1.
      double getLambda()
      Returns the λ associated with this object.
      double getMean()
      Returns the mean of the distribution function.
      static double getMean(double lambda)
      Computes and returns the mean E[X] = λ of the Poisson distribution with parameter λ.
      static double[] getMLE(int[] x, int n)
      Estimates the parameter λ of the Poisson distribution using the maximum likelihood method, from the n observations x[i], i = 0, 1,…, n - 1.
      double[] getParams()
      Return a table containing the parameter of the current distribution.
      double getStandardDeviation()
      Returns the standard deviation of the distribution function.
      static double getStandardDeviation(double lambda)
      Computes and returns the standard deviation of the Poisson distribution with parameter λ.
      double getVariance()
      Returns the variance of the distribution function.
      static double getVariance(double lambda)
      Computes and returns the variance = λ of the Poisson distribution with parameter λ.
      static int inverseF(double lambda, double u)
      Performs a linear search to get the inverse function without precomputed tables.
      int inverseFInt(double u)
      Returns the inverse distribution function F-1(u), where 0 <= u <= 1.
      static double prob(double lambda, int x)
      Computes and returns the Poisson probability p(x) for λ = lambda..
      double prob(int x)
      Returns p(x), the probability of x, which should be a real number in the interval [0, 1].
      void setLambda(double lambda)
      Sets the λ associated with this object.
      java.lang.String toString() 

      • Methods inherited from class java.lang.Object

        equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

    • Field Detail

      • MAXLAMBDA

        public static double MAXLAMBDA

    • Constructor Detail

      • PoissonDist

        public PoissonDist(double lambda)
        Creates an object that contains the probability and distribution functions, for the Poisson distribution with parameter lambda, which are computed and stored in dynamic arrays inside that object.

    • Method Detail

      • prob

        public double prob(int x)
        Description copied from class: DiscreteDistributionInt
        Returns p(x), the probability of x, which should be a real number in the interval [0, 1].
        Specified by:
        prob in class DiscreteDistributionInt
        Parameters:
        x - value at which the mass function must be evaluated
        Returns:
        the mass function evaluated at x

      • cdf

        public double cdf(int x)
        Description copied from class: DiscreteDistributionInt
        Returns the distribution function F evaluated at x (see).
        Specified by:
        cdf in class DiscreteDistributionInt
        Parameters:
        x - value at which the distribution function must be evaluated
        Returns:
        the distribution function evaluated at x

      • barF

        public double barF(int x)
        Description copied from class: DiscreteDistributionInt
        Returns bar(F)(x), the complementary distribution function. See the WARNING above.
        Overrides:
        barF in class DiscreteDistributionInt
        Parameters:
        x - value at which the complementary distribution function must be evaluated
        Returns:
        the complementary distribution function evaluated at x

      • inverseFInt

        public int inverseFInt(double u)
        Description copied from class: DiscreteDistributionInt
        Returns the inverse distribution function F-1(u), where 0 <= u <= 1. The default implementation uses binary search.
        Overrides:
        inverseFInt in class DiscreteDistributionInt
        Parameters:
        u - value in the interval (0, 1) for which the inverse distribution function is evaluated
        Returns:
        the inverse distribution function evaluated at u

      • getMean

        public double getMean()
        Description copied from interface: Distribution
        Returns the mean of the distribution function.

      • getVariance

        public double getVariance()
        Description copied from interface: Distribution
        Returns the variance of the distribution function.

      • getStandardDeviation

        public double getStandardDeviation()
        Description copied from interface: Distribution
        Returns the standard deviation of the distribution function.

      • prob

        public static double prob(double lambda,
                          int x)
        Computes and returns the Poisson probability p(x) for λ = lambda..

      • cdf

        public static double cdf(double lambda,
                         int x)
        Computes and returns the value of the Poisson distribution function F(x) for λ = lambda.

      • barF

        public static double barF(double lambda,
                          int x)
        Computes and returns the value of the complementary Poisson distribution function, for λ = lambda. WARNING: The complementary distribution function is defined as bar(F)(x) = P[X >= x].

      • inverseF

        public static int inverseF(double lambda,
                           double u)
        Performs a linear search to get the inverse function without precomputed tables.

      • getMLE

        public static double[] getMLE(int[] x,
                              int n)
        Estimates the parameter λ of the Poisson distribution using the maximum likelihood method, from the n observations x[i], i = 0, 1,…, n - 1. The maximum likelihood estimator hat(λ) satisfy the equation hat(λ) = bar(x)n, where bar(x)n is the average of x[0],…, x[n - 1] (see).
        Parameters:
        x - the list of observations used to evaluate parameters
        n - the number of observations used to evaluate parameters
        Returns:
        returns the parameter [ hat(λ)]

      • getInstanceFromMLE

        public static PoissonDist getInstanceFromMLE(int[] x,
                                             int n)
        Creates a new instance of a Poisson distribution with parameter λ estimated using the maximum likelihood method based on the n observations x[i], i = 0, 1,…, n - 1.
        Parameters:
        x - the list of observations to use to evaluate parameters
        n - the number of observations to use to evaluate parameters

      • getMean

        public static double getMean(double lambda)
        Computes and returns the mean E[X] = λ of the Poisson distribution with parameter λ.
        Returns:
        the mean of the Poisson distribution E[X] = λ

      • getVariance

        public static double getVariance(double lambda)
        Computes and returns the variance = λ of the Poisson distribution with parameter λ.
        Returns:
        the variance of the Poisson distribution Var[X] = λ

      • getStandardDeviation

        public static double getStandardDeviation(double lambda)
        Computes and returns the standard deviation of the Poisson distribution with parameter λ.
        Returns:
        the standard deviation of the Poisson distribution

      • getLambda

        public double getLambda()
        Returns the λ associated with this object.

      • setLambda

        public void setLambda(double lambda)
        Sets the λ associated with this object.

      • getParams

        public double[] getParams()
        Return a table containing the parameter of the current distribution.

      • toString

        public java.lang.String toString()
        Overrides:
        toString in class java.lang.Object
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