umontreal.iro.lecuyer.probdist
Class WeibullDist
- java.lang.Object
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- umontreal.iro.lecuyer.probdist.ContinuousDistribution
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- umontreal.iro.lecuyer.probdist.WeibullDist
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- All Implemented Interfaces:
- Distribution
public class WeibullDist extends ContinuousDistribution
This class extends the classContinuousDistributionfor the Weibull distribution with shape parameter α > 0, location parameter δ, and scale parameter λ > 0. The density function isf (x) = αλα(x - δ)α-1e-(λ(x-δ))α for x > δ.the distribution function isF(x) = 1 - e-(λ(x-δ))α for x > δ,and the inverse distribution function isF-1(u) = (- ln(1 - u))1/α/λ + δ for 0 <= u < 1.
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Field Summary
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Fields inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution
decPrec
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Constructor Summary
Constructors Constructor and Description WeibullDist(double alpha)Constructs a WeibullDist object with parameters α = alpha, λ = 1, and δ = 0.WeibullDist(double alpha, double lambda, double delta)Constructs a WeibullDist object with parameters α = alpha, λ = lambda, and δ = delta.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method and Description doublebarF(double x)Returns the complementary distribution function.static doublebarF(double alpha, double x)Same as barF (alpha, 1, 0, x).static doublebarF(double alpha, double lambda, double delta, double x)Computes the complementary distribution function.doublecdf(double x)Returns the distribution function F(x).static doublecdf(double alpha, double x)Same as cdf (alpha, 1, 0, x).static doublecdf(double alpha, double lambda, double delta, double x)Computes the distribution function.doubledensity(double x)Returns f (x), the density evaluated at x.static doubledensity(double alpha, double x)Same as density (alpha, 1, 0, x).static doubledensity(double alpha, double lambda, double delta, double x)Computes the density function.doublegetAlpha()Returns the parameter α.doublegetDelta()Returns the parameter δ.static WeibullDistgetInstanceFromMLE(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.doublegetLambda()Returns the parameter λ.doublegetMean()Returns the mean.static doublegetMean(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.doublegetStandardDeviation()Returns the standard deviation.static doublegetStandardDeviation(double alpha, double lambda, double delta)Computes and returns the standard deviation of the Weibull distribution with parameters α, λ and δ.doublegetVariance()Returns the variance.static doublegetVariance(double alpha, double lambda, double delta)Computes and returns the variance of the Weibull distribution with parameters α, λ and δ.doubleinverseF(double u)Returns the inverse distribution function x = F-1(u).static doubleinverseF(double alpha, double x)Same as inverseF (alpha, 1, 0, x).static doubleinverseF(double alpha, double lambda, double delta, double u)Computes the inverse of the distribution function.voidsetParams(double alpha, double lambda, double delta)Sets the parameters α, λ and δ for this object.java.lang.StringtoString()-
Methods inherited from class umontreal.iro.lecuyer.probdist.ContinuousDistribution
getXinf, getXsup, inverseBisection, inverseBrent, setXinf, setXsup
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Constructor Detail
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WeibullDist
public WeibullDist(double alpha)
Constructs a WeibullDist object with parameters α = alpha, λ = 1, and δ = 0.
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WeibullDist
public WeibullDist(double alpha, double lambda, double delta)Constructs a WeibullDist object with parameters α = alpha, λ = lambda, and δ = delta.
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Method Detail
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density
public double density(double x)
Description copied from class:ContinuousDistributionReturns f (x), the density evaluated at x.- Specified by:
densityin classContinuousDistribution- Parameters:
x- value at which the density is evaluated- Returns:
- density function evaluated at x
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cdf
public double cdf(double x)
Description copied from interface:DistributionReturns the distribution function F(x).- Parameters:
x- value at which the distribution function is evaluated- Returns:
- distribution function evaluated at x
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barF
public double barF(double x)
Description copied from class:ContinuousDistributionReturns the complementary distribution function. The default implementation computes bar(F)(x) = 1 - F(x).- Specified by:
barFin interfaceDistribution- Overrides:
barFin classContinuousDistribution- Parameters:
x- value at which the complementary distribution function is evaluated- Returns:
- complementary distribution function evaluated at x
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inverseF
public double inverseF(double u)
Description copied from class:ContinuousDistributionReturns the inverse distribution function x = F-1(u). Restrictions: u∈[0, 1].- Specified by:
inverseFin interfaceDistribution- Overrides:
inverseFin classContinuousDistribution- Parameters:
u- value at which the inverse distribution function is evaluated- Returns:
- the inverse distribution function evaluated at u
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getMean
public double getMean()
Description copied from class:ContinuousDistributionReturns the mean.- Specified by:
getMeanin interfaceDistribution- Overrides:
getMeanin classContinuousDistribution- Returns:
- the mean
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getVariance
public double getVariance()
Description copied from class:ContinuousDistributionReturns the variance.- Specified by:
getVariancein interfaceDistribution- Overrides:
getVariancein classContinuousDistribution- Returns:
- the variance
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getStandardDeviation
public double getStandardDeviation()
Description copied from class:ContinuousDistributionReturns the standard deviation.- Specified by:
getStandardDeviationin interfaceDistribution- Overrides:
getStandardDeviationin classContinuousDistribution- Returns:
- the standard deviation
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density
public static double density(double alpha, double lambda, double delta, double x)Computes the density function.
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density
public static double density(double alpha, double x)Same as density (alpha, 1, 0, x).
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cdf
public static double cdf(double alpha, double lambda, double delta, double x)Computes the distribution function.
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cdf
public static double cdf(double alpha, double x)Same as cdf (alpha, 1, 0, x).
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barF
public static double barF(double alpha, double lambda, double delta, double x)Computes the complementary distribution function.
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barF
public static double barF(double alpha, double x)Same as barF (alpha, 1, 0, x).
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inverseF
public static double inverseF(double alpha, double lambda, double delta, double u)Computes the inverse of the distribution function.
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inverseF
public static double inverseF(double alpha, double x)Same as inverseF (alpha, 1, 0, x).
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getMLE
public 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. The estimates are returned in a two-element array, in regular order: [α, λ].- Parameters:
x- the list of observations to use to evaluate parametersn- the number of observations to use to evaluate parameters- Returns:
- returns the parameter [ hat(α), hat(λ), hat(δ) = 0]
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getInstanceFromMLE
public 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.- Parameters:
x- the list of observations to use to evaluate parametersn- the number of observations to use to evaluate parameters
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getMean
public static double getMean(double alpha, double lambda, double delta)Computes and returns the mean of the Weibull distribution with parameters α, λ and δ.- Returns:
- the mean of the Weibull distribution E[X] = δ + Γ(1 + 1/α)/λ
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getVariance
public static double getVariance(double alpha, double lambda, double delta)Computes and returns the variance of the Weibull distribution with parameters α, λ and δ.- Returns:
- the variance of the Weibull distribution Var[X] = 1/λ2| Γ(2/α +1) - Γ2(1/α + 1)|
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getStandardDeviation
public 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.- Returns:
- the standard deviation of the Weibull distribution
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getAlpha
public double getAlpha()
Returns the parameter α.
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getLambda
public double getLambda()
Returns the parameter λ.
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getDelta
public double getDelta()
Returns the parameter δ.
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setParams
public void setParams(double alpha, double lambda, double delta)Sets the parameters α, λ and δ for this object.
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getParams
public double[] getParams()
Return a table containing the parameters of the current distribution. This table is put in regular order: [α, λ, δ].
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toString
public java.lang.String toString()
- Overrides:
toStringin classjava.lang.Object
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