SSJ
V. 1.2.5.

umontreal.iro.lecuyer.probdist
Class ExponentialDist

java.lang.Object
  extended by umontreal.iro.lecuyer.probdist.ContinuousDistribution
      extended by umontreal.iro.lecuyer.probdist.ExponentialDist
All Implemented Interfaces:
Distribution

public class ExponentialDist
extends ContinuousDistribution

Extends the class ContinuousDistribution for the exponential distribution with mean 1/λ where λ > 0. Its density is

f (x) = λe-λx        for x >= 0,

its distribution function is

F(x) = 1 - e-λx,        for x >= 0,

and its inverse distribution function is

F-1(u) = - ln(1 - u)/λ,        for 0 < u < 1.


Field Summary
 
Fields inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution
decPrec
 
Constructor Summary
ExponentialDist()
          Constructs an ExponentialDist object with parameter λ = 1.
ExponentialDist(double lambda)
          Constructs an ExponentialDist object with parameter λ = lambda.
 
Method Summary
 double barF(double x)
          Returns bar(F)(x) = 1 - F(x).
static double barF(double lambda, double x)
          Computes the complementary distribution function.
 double cdf(double x)
          Computes and returns the distribution function F(x).
static double cdf(double lambda, double x)
          Computes the distribution function.
 double density(double x)
          Returns f (x), the density of X evaluated at x.
static double density(double lambda, double x)
          Computes the density function.
static ExponentialDist getInstanceFromMLE(double[] x, int n)
          Creates a new instance of an exponential distribution with parameter λ estimated using the maximum likelihood method based on the n observations in table x[i], i = 0, 1,…, n - 1.
 double getLambda()
          Returns the value of λ for this object.
static double[] getMaximumLikelihoodEstimate(double[] x, int n)
          Estimates and returns the parameter [ hat(λ)] of the exponential distribution using the maximum likelihood method based on the n observations in table x[i], i = 0, 1,…, n - 1.
 double getMean()
          Returns the mean of the distribution function.
static double getMean(double lambda)
          Computes and returns the mean, E[X] = 1/λ, of the exponential distribution with parameter λ.
 double getStandardDeviation()
          Returns the standard deviation of the distribution function.
static double getStandardDeviation(double lambda)
          Computes and returns the standard deviation of the exponential distribution with parameter λ.
 double getVariance()
          Returns the variance of the distribution function.
static double getVariance(double lambda)
          Computes and returns the variance, Var[X] = 1/λ2, of the exponential distribution with parameter λ.
 double inverseF(double u)
          Computes and returns the inverse distribution function F-1(u), defined in.
static double inverseF(double lambda, double u)
          Computes the inverse distribution function.
 void setLambda(double lambda)
          Sets the value of λ for this object.
 
Methods inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution
inverseBisection, inverseBrent
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

ExponentialDist

public ExponentialDist()
Constructs an ExponentialDist object with parameter λ = 1.


ExponentialDist

public ExponentialDist(double lambda)
Constructs an ExponentialDist object with parameter λ = lambda.

Method Detail

density

public double density(double x)
Description copied from class: ContinuousDistribution
Returns f (x), the density of X 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
Computes and 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 interface: Distribution
Returns 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 interface: Distribution
Computes and returns the inverse distribution function F-1(u), defined in.

Specified by:
inverseF in interface Distribution
Overrides:
inverseF in class ContinuousDistribution
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.


density

public static double density(double lambda,
                             double x)
Computes the density function.


cdf

public static double cdf(double lambda,
                         double x)
Computes the distribution function.


barF

public static double barF(double lambda,
                          double x)
Computes the complementary distribution function.


inverseF

public static double inverseF(double lambda,
                              double u)
Computes the inverse distribution function.


getInstanceFromMLE

public static ExponentialDist getInstanceFromMLE(double[] x,
                                                 int n)
Creates a new instance of an exponential distribution with parameter λ estimated using the maximum likelihood method based on the n observations in table 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

getMaximumLikelihoodEstimate

public static double[] getMaximumLikelihoodEstimate(double[] x,
                                                    int n)
Estimates and returns the parameter [ hat(λ)] of the exponential distribution using the maximum likelihood method based on the n observations in table x[i], i = 0, 1,…, n - 1.

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)]

getMean

public static double getMean(double lambda)
Computes and returns the mean, E[X] = 1/λ, of the exponential distribution with parameter λ.

Returns:
the mean of the exponential distribution E[X] = 1/λ

getVariance

public static double getVariance(double lambda)
Computes and returns the variance, Var[X] = 1/λ2, of the exponential distribution with parameter λ.

Returns:
the variance of the Exponential distribution Var[X] = 1/λ2

getStandardDeviation

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

Returns:
the standard deviation of the exponential distribution

getLambda

public double getLambda()
Returns the value of λ for this object.


setLambda

public void setLambda(double lambda)
Sets the value of λ for this object.


SSJ
V. 1.2.5.

To submit a bug or ask questions, send an e-mail to Pierre L'Ecuyer.