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

Class NakagamiDist

  • All Implemented Interfaces:
    Distribution


    public class NakagamiDist
    extends ContinuousDistribution
    Extends the class ContinuousDistribution for the Nakagami distribution with location parameter a, scale parameter λ > 0 and shape parameter c > 0. The density is

    f (x) = 2λc/Γ(c)  (x - a)2c-1  e-λ(x-a)2        for x > a,

    f (x) = 0         for x <= a,

    where Γ is the gamma function.
    • Constructor Summary

      Constructors 
      Constructor and Description
      NakagamiDist(double a, double lambda, double c)
      Constructs a NakagamiDist object with parameters a = a, λ = lambda and c = c.
    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method and Description
      double barF(double x)
      Returns the complementary distribution function.
      static double barF(double a, double lambda, double c, double x)
      Computes the complementary distribution function.
      double cdf(double x)
      Returns the distribution function F(x).
      static double cdf(double a, double lambda, double c, double x)
      Computes the distribution function.
      double density(double x)
      Returns f (x), the density evaluated at x.
      static double density(double a, double lambda, double c, double x)
      Computes the density function of the Nakagami distribution.
      double getA()
      Returns the location parameter a of this object.
      double getC()
      Returns the shape parameter c of this object.
      double getLambda()
      Returns the scale parameter λ of this object.
      double getMean()
      Returns the mean.
      static double getMean(double a, double lambda, double c)
      .
      double[] getParams()
      Return a table containing the parameters of the current distribution.
      double getStandardDeviation()
      Returns the standard deviation.
      static double getStandardDeviation(double a, double lambda, double c)
      Computes the standard deviation of the Nakagami distribution with parameters a, λ and c.
      double getVariance()
      Returns the variance.
      static double getVariance(double a, double lambda, double c)
      .
      double inverseF(double u)
      Returns the inverse distribution function x = F-1(u).
      static double inverseF(double a, double lambda, double c, double u)
      Computes the inverse of the distribution function.
      void setParams(double a, double lambda, double c)
      Sets the parameters a, λ and c of this object.
      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

      • NakagamiDist

        public NakagamiDist(double a,
                            double lambda,
                            double c)
        Constructs a NakagamiDist object with parameters a = a, λ = lambda and c = c.
    • Method Detail

      • density

        public double density(double x)
        Description copied from class: ContinuousDistribution
        Returns f (x), the density evaluated at x.
        Specified by:
        density in class ContinuousDistribution
        Parameters:
        x - value at which the density is evaluated
        Returns:
        density function evaluated at x
      • cdf

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

        public double barF(double x)
        Description copied from class: ContinuousDistribution
        Returns the complementary distribution function. The default implementation computes bar(F)(x) = 1 - F(x).
        Specified by:
        barF in interface Distribution
        Overrides:
        barF in class ContinuousDistribution
        Parameters:
        x - value at which the complementary distribution function is evaluated
        Returns:
        complementary distribution function evaluated at x
      • inverseF

        public double inverseF(double u)
        Description copied from class: ContinuousDistribution
        Returns the inverse distribution function x = F-1(u). Restrictions: u∈[0, 1].
        Specified by:
        inverseF in interface Distribution
        Overrides:
        inverseF in class ContinuousDistribution
        Parameters:
        u - value at which the inverse distribution function is evaluated
        Returns:
        the inverse distribution function evaluated at u
      • density

        public static double density(double a,
                                     double lambda,
                                     double c,
                                     double x)
        Computes the density function of the Nakagami distribution.
        Parameters:
        a - the location parameter
        lambda - the scale parameter
        c - the shape parameter
        x - the value at which the density is evaluated
        Returns:
        returns the density function
      • cdf

        public static double cdf(double a,
                                 double lambda,
                                 double c,
                                 double x)
        Computes the distribution function.
        Parameters:
        a - the location parameter
        lambda - the scale parameter
        c - the shape parameter
        x - the value at which the distribution is evaluated
        Returns:
        returns the cdf function
      • barF

        public static double barF(double a,
                                  double lambda,
                                  double c,
                                  double x)
        Computes the complementary distribution function.
        Parameters:
        a - the location parameter
        lambda - the scale parameter
        c - the shape parameter
        x - the value at which the complementary distribution is evaluated
        Returns:
        returns the complementary distribution function
      • inverseF

        public static double inverseF(double a,
                                      double lambda,
                                      double c,
                                      double u)
        Computes the inverse of the distribution function.
        Parameters:
        a - the location parameter
        lambda - the scale parameter
        c - the shape parameter
        u - the value at which the inverse distribution is evaluated
        Returns:
        returns the inverse distribution function
      • getMean

        public static double getMean(double a,
                                     double lambda,
                                     double c)
        . Computes and returns the mean

        E[X] = a + $\displaystyle {\frac{{1}}{{\sqrt{\lambda}}}}$  $\displaystyle {\frac{{\Gamma(c+1/2)}}{{\Gamma(c)}}}$.

        Parameters:
        a - the location parameter
        lambda - the scale parameter
        c - the shape parameter
        Returns:
        returns the mean
      • getVariance

        public static double getVariance(double a,
                                         double lambda,
                                         double c)
        . Computes and returns the variance

        Var[X] = $\displaystyle {\frac{{1}}{{\lambda}}}$[c - ([tex2html_wrap_indisplay261])2].

        Parameters:
        a - the location parameter
        lambda - the scale parameter
        c - the shape parameter
        Returns:
        returns the variance
      • getStandardDeviation

        public static double getStandardDeviation(double a,
                                                  double lambda,
                                                  double c)
        Computes the standard deviation of the Nakagami distribution with parameters a, λ and c.
        Parameters:
        a - the location parameter
        lambda - the scale parameter
        c - the shape parameter
        Returns:
        returns the standard deviation
      • getA

        public double getA()
        Returns the location parameter a of this object.
        Returns:
        returns the location parameter
      • getLambda

        public double getLambda()
        Returns the scale parameter λ of this object.
        Returns:
        returns the scale parameter
      • getC

        public double getC()
        Returns the shape parameter c of this object.
        Returns:
        returns the shape parameter
      • setParams

        public void setParams(double a,
                              double lambda,
                              double c)
        Sets the parameters a, λ and c of this object.
        Parameters:
        a - the location parameter
        lambda - the scale parameter
        c - the shape parameter
      • getParams

        public double[] getParams()
        Return a table containing the parameters of the current distribution. This table is put in regular order: [a, λ, c].
        Returns:
        returns the parameters [a, λ, c]
      • toString

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

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