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java.lang.Objectumontreal.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 bar(F)(x) = 1 - F(x). |
static double |
barF(double alpha,
double x)
Same as barF (alpha, 1.0, 0.0, x). |
static double |
barF(double alpha,
double lambda,
double delta,
double x)
Computes the complementary distribution function. |
double |
cdf(double x)
Computes and returns the distribution function F(x). |
static double |
cdf(double alpha,
double x)
Same as cdf (alpha, 1.0, 0.0, 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 of X evaluated at x. |
static double |
density(double alpha,
double x)
Same as density (alpha, 1.0, 0.0, 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 estimated using the maximum likelihood method based on the n observations in table x[i], i = 0, 1,…, n - 1. |
double |
getLambda()
Returns the parameter λ. |
static double[] |
getMaximumLikelihoodEstimate(double[] x,
int n)
Estimates and returns the parameters [ hat(α), hat(λ), hat(δ) = 0] of the Weibull 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 lambda,
double delta)
Computes and returns the mean of the Weibull distribution with parameters α, λ and δ. |
double |
getStandardDeviation()
Returns the standard deviation of the distribution function. |
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 of the distribution function. |
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)
Computes and returns the inverse distribution function F-1(u), defined in. |
static double |
inverseF(double alpha,
double x)
Same as inverseF (alpha, 1.0, 0.0, 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. |
Methods inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution |
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inverseBisection, inverseBrent |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, 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)
Distribution
barF
in interface Distribution
barF
in class ContinuousDistribution
x
- value at which the complementary distribution function is evaluated
public double inverseF(double u)
Distribution
inverseF
in interface Distribution
inverseF
in class ContinuousDistribution
u
- value in the interval (0, 1) for which the inverse
distribution function is evaluated
public double getMean()
Distribution
public double getVariance()
Distribution
public double getStandardDeviation()
Distribution
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 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[] getMaximumLikelihoodEstimate(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 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)
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