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java.lang.Object umontreal.iro.lecuyer.probdist.ContinuousDistribution umontreal.iro.lecuyer.probdist.LoglogisticDist
public class LoglogisticDist
Extends the class ContinuousDistribution
for the
Log-Logistic distribution with shape parameter
α > 0
and scale parameter β > 0.
Its density is
Field Summary |
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Fields inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution |
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decPrec |
Constructor Summary | |
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LoglogisticDist(double alpha,
double beta)
Constructs a log-logistic distribution with parameters α and β. |
Method Summary | |
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double |
barF(double x)
Returns the complementary distribution function. |
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)
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 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 x[i], i = 0, 1,…, n - 1. |
double |
getMean()
Returns the mean. |
static double |
getMean(double alpha,
double beta)
Computes and returns the mean of the log-logistic distribution with parameters α and β. |
static double[] |
getMLE(double[] x,
int n)
Estimates the parameters (α, β) of the log-logistic distribution using the maximum likelihood method, from the n observations x[i], i = 0, 1,…, n - 1. |
double[] |
getParams()
Return a table containing the parameters of the current distribution. |
double |
getStandardDeviation()
Returns the standard deviation. |
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. |
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)
Returns the inverse distribution function x = F-1(u). |
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. |
String |
toString()
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Methods inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution |
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getXinf, getXsup, inverseBisection, inverseBrent, setXinf, setXsup |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public LoglogisticDist(double alpha, double beta)
Method Detail |
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public double density(double x)
ContinuousDistribution
density
in class ContinuousDistribution
x
- value at which the density is evaluated
public double cdf(double x)
Distribution
x
- value at which the distribution function is evaluated
public double barF(double x)
ContinuousDistribution
barF
in interface Distribution
barF
in class ContinuousDistribution
x
- value at which the complementary distribution function is evaluated
public double inverseF(double u)
ContinuousDistribution
inverseF
in interface Distribution
inverseF
in class ContinuousDistribution
u
- value at which the inverse distribution function is evaluated
public double getMean()
ContinuousDistribution
getMean
in interface Distribution
getMean
in class ContinuousDistribution
public double getVariance()
ContinuousDistribution
getVariance
in interface Distribution
getVariance
in class ContinuousDistribution
public double getStandardDeviation()
ContinuousDistribution
getStandardDeviation
in interface Distribution
getStandardDeviation
in class ContinuousDistribution
public static double density(double alpha, double beta, double x)
public static double cdf(double alpha, double beta, double x)
public static double barF(double alpha, double beta, double x)
public static double inverseF(double alpha, double beta, double u)
public static double[] getMLE(double[] x, int n)
x
- the list of observations to use to evaluate parametersn
- the number of observations to use to evaluate parameters
public static LoglogisticDist getInstanceFromMLE(double[] x, int n)
x
- the list of observations to use to evaluate parametersn
- the number of observations to use to evaluate parameterspublic static double getMean(double alpha, double beta)
public static double getVariance(double alpha, double beta)
public static double getStandardDeviation(double alpha, double beta)
public double getAlpha()
public double getBeta()
public void setParams(double alpha, double beta)
public double[] getParams()
public String toString()
toString
in class Object
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