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java.lang.Object umontreal.iro.lecuyer.probdist.ContinuousDistribution umontreal.iro.lecuyer.probdist.ExponentialDist
public class ExponentialDist
Extends the class ContinuousDistribution
for
the exponential distribution
with mean 1/λ where
λ > 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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ExponentialDist()
Constructs an ExponentialDist object with parameter λ = 1. |
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ExponentialDist(double lambda)
Constructs an ExponentialDist object with parameter λ = lambda. |
Method Summary | |
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double |
barF(double x)
Returns the complementary distribution function. |
static double |
barF(double lambda,
double x)
Computes the complementary distribution function. |
double |
cdf(double x)
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 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 x[i], i = 0, 1,…, n - 1. |
double |
getLambda()
Returns the value of λ for this object. |
double |
getMean()
Returns the mean. |
static double |
getMean(double lambda)
Computes and returns the mean, E[X] = 1/λ, of the exponential distribution with parameter λ. |
static double[] |
getMLE(double[] x,
int n)
Estimates the parameter λ of the exponential 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 lambda)
Computes and returns the standard deviation of the exponential distribution with parameter λ. |
double |
getVariance()
Returns the variance. |
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)
Returns the inverse distribution function x = F-1(u). |
static double |
inverseF(double lambda,
double u)
Computes the inverse distribution function. |
void |
setLambda(double lambda)
Sets the value of λ for 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 ExponentialDist()
public ExponentialDist(double lambda)
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 lambda, double x)
public static double cdf(double lambda, double x)
public static double barF(double lambda, double x)
public static double inverseF(double lambda, double u)
public static double[] getMLE(double[] x, int n)
x
- the list of observations used to evaluate parametersn
- the number of observations used to evaluate parameters
public static ExponentialDist 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 lambda)
public static double getVariance(double lambda)
public static double getStandardDeviation(double lambda)
public double getLambda()
public void setLambda(double lambda)
public double[] getParams()
public String toString()
toString
in class Object
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