SSJ
V. 1.2.5.

umontreal.iro.lecuyer.probdist
Class LoglogisticDist

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

public class LoglogisticDist
extends ContinuousDistribution

Extends the class ContinuousDistribution for the Log-Logistic distribution with shape parameter α > 0 and scale parameter β > 0. Its density is

f (x) = (α(x/β)α-1)/(β[1 + (x/β)α]2)                for x > 0

and its distribution function is

F(x) = 1/(1 + (x/β)-α)                for x > 0.

The complementary distribution is

bar(F)(x) = 1/(1 + (x/β)α)                for x > 0.


Field Summary
 
Fields inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution
decPrec
 
Constructor Summary
LoglogisticDist(double alpha, double beta)
          Constructs a log-logistic distribution with parameters α and β.
 
Method Summary
 double barF(double x)
          Returns bar(F)(x) = 1 - F(x).
static double barF(double alpha, double beta, double x)
          Computes the complementary distribution function of the log-logistic distribution with parameters α and β.
 double cdf(double x)
          Computes and returns the distribution function F(x).
static double cdf(double alpha, double beta, double x)
          Computes the distribution function of the log-logistic distribution with parameters α and β.
 double density(double x)
          Returns f (x), the density of X evaluated at x.
static double density(double alpha, double beta, double x)
          Computes the density function for a log-logisitic distribution with parameters α and β.
 double getAlpha()
          Return the parameter α of this object.
 double getBeta()
          Returns the parameter β of this object.
static LoglogisticDist getInstanceFromMLE(double[] x, int n)
          Creates a new instance of a log-logistic distribution with parameters α and β estimated using the maximum likelihood method based on the n observations in table x[i], i = 0, 1,…, n - 1.
static double[] getMaximumLikelihoodEstimate(double[] x, int n)
          Estimates and returns the parameters [ hat(α), hat(β)] of the log-logistic 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 alpha, double beta)
          Computes and returns the mean of the log-logistic distribution with parameters α and β.
 double getStandardDeviation()
          Returns the standard deviation of the distribution function.
static double getStandardDeviation(double alpha, double beta)
          Computes and returns the standard deviation of the log-logistic distribution with parameters α and β.
 double getVariance()
          Returns the variance of the distribution function.
static double getVariance(double alpha, double beta)
          Computes and returns the variance of the log-logistic distribution with parameters α and β.
 double inverseF(double u)
          Computes and returns the inverse distribution function F-1(u), defined in.
static double inverseF(double alpha, double beta, double u)
          Computes the inverse of the log-logistic distribution with parameters α and β.
 void setParams(double alpha, double beta)
          Sets the parameters α and β of 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

LoglogisticDist

public LoglogisticDist(double alpha,
                       double beta)
Constructs a log-logistic distribution with parameters α and β.

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 alpha,
                             double beta,
                             double x)
Computes the density function for a log-logisitic distribution with parameters α and β.


cdf

public static double cdf(double alpha,
                         double beta,
                         double x)
Computes the distribution function of the log-logistic distribution with parameters α and β.


barF

public static double barF(double alpha,
                          double beta,
                          double x)
Computes the complementary distribution function of the log-logistic distribution with parameters α and β.


inverseF

public static double inverseF(double alpha,
                              double beta,
                              double u)
Computes the inverse of the log-logistic distribution with parameters α and β.


getInstanceFromMLE

public static LoglogisticDist getInstanceFromMLE(double[] x,
                                                 int n)
Creates a new instance of a log-logistic distribution with parameters α and β 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 parameters [ hat(α), hat(β)] of the log-logistic 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 to use to evaluate parameters
n - the number of observations to use to evaluate parameters
Returns:
returns the parameters [ hat(α), hat(β)]

getMean

public static double getMean(double alpha,
                             double beta)
Computes and returns the mean of the log-logistic distribution with parameters α and β.

Returns:
the mean of the log-logistic distribution E[X] = βθ cosec(θ), where θ = π/α

getVariance

public static double getVariance(double alpha,
                                 double beta)
Computes and returns the variance of the log-logistic distribution with parameters α and β.

Returns:
the variance of the log-logistic distribution Var[X] = β2θ(2cosec(2θ) - θ[cosec(θ)]2), where θ = π/α

getStandardDeviation

public static double getStandardDeviation(double alpha,
                                          double beta)
Computes and returns the standard deviation of the log-logistic distribution with parameters α and β.

Returns:
the standard deviation of the log-logistic distribution

getAlpha

public double getAlpha()
Return the parameter α of this object.


getBeta

public double getBeta()
Returns the parameter β of this object.


setParams

public void setParams(double alpha,
                      double beta)
Sets the parameters α and β of this object.


SSJ
V. 1.2.5.

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