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java.lang.Object umontreal.iro.lecuyer.probdist.ContinuousDistribution umontreal.iro.lecuyer.probdist.WeibullDist
public class WeibullDist
This class extends the class ContinuousDistribution
for
the Weibull distribution with shape parameter
α > 0, location parameter δ, and scale parameter
λ > 0.
The density function 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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WeibullDist(double alpha)
Constructs a WeibullDist object with parameters α = alpha, λ = 1, and δ = 0. |
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WeibullDist(double alpha,
double lambda,
double delta)
Constructs a WeibullDist object with parameters α = alpha, λ = lambda, and δ = delta. |
Method Summary | |
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double |
barF(double x)
Returns the complementary distribution function. |
static double |
barF(double alpha,
double x)
Same as barF (alpha, 1, 0, x). |
static double |
barF(double alpha,
double lambda,
double delta,
double x)
Computes the complementary distribution function. |
double |
cdf(double x)
Returns the distribution function F(x). |
static double |
cdf(double alpha,
double x)
Same as cdf (alpha, 1, 0, x). |
static double |
cdf(double alpha,
double lambda,
double delta,
double x)
Computes the distribution function. |
double |
density(double x)
Returns f (x), the density evaluated at x. |
static double |
density(double alpha,
double x)
Same as density (alpha, 1, 0, x). |
static double |
density(double alpha,
double lambda,
double delta,
double x)
Computes the density function. |
double |
getAlpha()
Returns the parameter α. |
double |
getDelta()
Returns the parameter δ. |
static WeibullDist |
getInstanceFromMLE(double[] x,
int n)
Creates a new instance of a Weibull distribution with parameters α, λ and δ = 0 estimated using the maximum likelihood method based on the n observations x[i], i = 0, 1,…, n - 1. |
double |
getLambda()
Returns the parameter λ. |
double |
getMean()
Returns the mean. |
static double |
getMean(double alpha,
double lambda,
double delta)
Computes and returns the mean of the Weibull distribution with parameters α, λ and δ. |
static double[] |
getMLE(double[] x,
int n)
Estimates the parameters (α, λ) of the Weibull distribution, assuming that δ = 0, 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 lambda,
double delta)
Computes and returns the standard deviation of the Weibull distribution with parameters α, λ and δ. |
double |
getVariance()
Returns the variance. |
static double |
getVariance(double alpha,
double lambda,
double delta)
Computes and returns the variance of the Weibull distribution with parameters α, λ and δ. |
double |
inverseF(double u)
Returns the inverse distribution function x = F-1(u). |
static double |
inverseF(double alpha,
double x)
Same as inverseF (alpha, 1, 0, x). |
static double |
inverseF(double alpha,
double lambda,
double delta,
double u)
Computes the inverse of the distribution function. |
void |
setParams(double alpha,
double lambda,
double delta)
Sets the parameters α, λ and δ 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 WeibullDist(double alpha)
public WeibullDist(double alpha, double lambda, double delta)
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 lambda, double delta, double x)
public static double density(double alpha, double x)
public static double cdf(double alpha, double lambda, double delta, double x)
public static double cdf(double alpha, double x)
public static double barF(double alpha, double lambda, double delta, double x)
public static double barF(double alpha, double x)
public static double inverseF(double alpha, double lambda, double delta, double u)
public static double inverseF(double alpha, double x)
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 WeibullDist 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 lambda, double delta)
public static double getVariance(double alpha, double lambda, double delta)
public static double getStandardDeviation(double alpha, double lambda, double delta)
public double getAlpha()
public double getLambda()
public double getDelta()
public void setParams(double alpha, double lambda, double delta)
public double[] getParams()
public String toString()
toString
in class Object
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