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

Class DiscreteDistribution

  • All Implemented Interfaces:
    Distribution
    Direct Known Subclasses:
    EmpiricalDist


    public class DiscreteDistribution
    extends java.lang.Object
    implements Distribution
    Classes implementing discrete distributions over a finite set of real numbers should inherit from this class. For discrete distributions over integers, see DiscreteDistributionInt.

    We assume that the random variable X of interest can take one of the n values x0 < ... < xn-1 (which are sorted by increasing order). It takes the value xk with probability pk = P[X = xk]. In addition to the methods specified in the interface Distribution, a method that returns the probability pk is supplied.

    Note that the default implementation of the complementary distribution function returns 1.0 - cdf(x - 1), which is not accurate when F(x) is near 1.

    • Constructor Summary

      Constructors 
      Constructor and Description
      DiscreteDistribution(double[] params)
      Constructs a discrete distribution whose parameters are given in a single ordered array: params[0] contains n, the number of values to consider.
      DiscreteDistribution(double[] obs, double[] prob, int n)
      Constructs a discrete distribution over the n values contained in array obs, with probabilities given in array prob.
    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method and Description
      double barF(double x)
      Returns bar(F)(x) = 1 - F(x).
      double cdf(double x)
      Returns the distribution function F(x).
      double getMean()
      Computes the mean E[X] = ∑i=1npixi of the distribution.
      double[] getParams()
      Returns a table containing the parameters of the current distribution.
      double getStandardDeviation()
      Computes the standard deviation of the distribution.
      double getVariance()
      Computes the variance Var[X] = ∑i=1npi(xi - E[X])2 of the distribution.
      double getXinf()
      Returns the lower limit xa of the support of the distribution.
      double getXsup()
      Returns the upper limit xb of the support of the distribution.
      double inverseF(double u)
      Returns the inverse distribution function F-1(u), defined in.
      double prob(int k)
      Returns pk, the probability of the k-th observation, for 0 <= k < n.
      java.lang.String toString()
      Returns a String containing information about the current distribution.
      • Methods inherited from class java.lang.Object

        equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
    • Constructor Detail

      • DiscreteDistribution

        public DiscreteDistribution(double[] obs,
                                    double[] prob,
                                    int n)
        Constructs a discrete distribution over the n values contained in array obs, with probabilities given in array prob. Both arrays must have at least n elements, the probabilities must sum to 1, and the observations are assumed to be sorted by increasing order.
      • DiscreteDistribution

        public DiscreteDistribution(double[] params)
        Constructs a discrete distribution whose parameters are given in a single ordered array: params[0] contains n, the number of values to consider. Then the next n values of params are the observation values, and the last n values of params are the probabilities values.
    • Method Detail

      • prob

        public double prob(int k)
        Returns pk, the probability of the k-th observation, for 0 <= k < n. The result should be a real number in the interval [0, 1].
        Parameters:
        k - observation number, 0 <= k < n
        Returns:
        the probability of observation k
      • cdf

        public double cdf(double x)
        Description copied from interface: Distribution
        Returns the distribution function F(x).
        Specified by:
        cdf in interface Distribution
        Parameters:
        x - value at which the distribution function must be evaluated
        Returns:
        the distribution function evaluated at x
      • barF

        public double barF(double x)
        Description copied from interface: Distribution
        Returns bar(F)(x) = 1 - F(x).
        Specified by:
        barF in interface Distribution
        Parameters:
        x - value at which the complementary distribution function must be evaluated
        Returns:
        the complementary distribution function evaluated at x
      • inverseF

        public double inverseF(double u)
        Description copied from interface: Distribution
        Returns the inverse distribution function F-1(u), defined in.
        Specified by:
        inverseF in interface Distribution
        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()
        Computes the mean E[X] = ∑i=1npixi of the distribution.
        Specified by:
        getMean in interface Distribution
      • getVariance

        public double getVariance()
        Computes the variance Var[X] = ∑i=1npi(xi - E[X])2 of the distribution.
        Specified by:
        getVariance in interface Distribution
      • getStandardDeviation

        public double getStandardDeviation()
        Computes the standard deviation of the distribution.
        Specified by:
        getStandardDeviation in interface Distribution
      • getParams

        public double[] getParams()
        Returns a table containing the parameters of the current distribution. This table is built in regular order, according to constructor DiscreteDistribution(double[] params) order.
        Specified by:
        getParams in interface Distribution
      • getXinf

        public double getXinf()
        Returns the lower limit xa of the support of the distribution. The probability is 0 for all x < xa.
        Returns:
        x lower limit of support
      • getXsup

        public double getXsup()
        Returns the upper limit xb of the support of the distribution. The probability is 0 for all x > xb.
        Returns:
        x upper limit of support
      • toString

        public java.lang.String toString()
        Returns a String containing information about the current distribution.
        Overrides:
        toString in class java.lang.Object

DMelt 3.0 © DataMelt by jWork.ORG

You see the box below because you did not login.