Class WeibullDistributionImpl
java.lang.Object
org.apache.commons.math.distribution.AbstractDistribution
org.apache.commons.math.distribution.AbstractContinuousDistribution
org.apache.commons.math.distribution.WeibullDistributionImpl
- All Implemented Interfaces:
Serializable
,ContinuousDistribution
,Distribution
,WeibullDistribution
public class WeibullDistributionImpl
extends AbstractContinuousDistribution
implements WeibullDistribution, Serializable
Default implementation of
WeibullDistribution
.- Since:
- 1.1
- Version:
- $Revision: 1054524 $ $Date: 2011-01-03 05:59:18 +0100 (lun. 03 janv. 2011) $
- See Also:
-
Field Summary
FieldsModifier and TypeFieldDescriptionstatic final double
Default inverse cumulative probability accuracyFields inherited from class org.apache.commons.math.distribution.AbstractContinuousDistribution
randomData
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Constructor Summary
ConstructorsConstructorDescriptionWeibullDistributionImpl
(double alpha, double beta) Creates weibull distribution with the given shape and scale and a location equal to zero.WeibullDistributionImpl
(double alpha, double beta, double inverseCumAccuracy) Creates weibull distribution with the given shape, scale and inverse cumulative probability accuracy and a location equal to zero. -
Method Summary
Modifier and TypeMethodDescriptionprotected double
Calculates the mean.double
cumulativeProbability
(double x) For this distribution, X, this method returns P(X <x
).double
density
(double x) Returns the probability density for a particular point.protected double
getDomainLowerBound
(double p) Access the domain value lower bound, based onp
, used to bracket a CDF root.protected double
getDomainUpperBound
(double p) Access the domain value upper bound, based onp
, used to bracket a CDF root.protected double
getInitialDomain
(double p) Access the initial domain value, based onp
, used to bracket a CDF root.double
Returns the mean of the distribution.double
Returns the variance of the distribution.double
getScale()
Access the scale parameter.double
getShape()
Access the shape parameter.protected double
Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.double
Returns the lower bound of the support for the distribution.double
Returns the upper bound of the support for the distribution.double
inverseCumulativeProbability
(double p) For this distribution, X, this method returns the critical point x, such that P(X < x) =p
.void
setScale
(double beta) Deprecated.as of 2.1 (class will become immutable in 3.0)void
setShape
(double alpha) Deprecated.as of 2.1 (class will become immutable in 3.0)Methods inherited from class org.apache.commons.math.distribution.AbstractContinuousDistribution
reseedRandomGenerator, sample, sample
Methods inherited from class org.apache.commons.math.distribution.AbstractDistribution
cumulativeProbability
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.apache.commons.math.distribution.Distribution
cumulativeProbability
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Field Details
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DEFAULT_INVERSE_ABSOLUTE_ACCURACY
public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACYDefault inverse cumulative probability accuracy- Since:
- 2.1
- See Also:
-
-
Constructor Details
-
WeibullDistributionImpl
public WeibullDistributionImpl(double alpha, double beta) Creates weibull distribution with the given shape and scale and a location equal to zero.- Parameters:
alpha
- the shape parameter.beta
- the scale parameter.
-
WeibullDistributionImpl
public WeibullDistributionImpl(double alpha, double beta, double inverseCumAccuracy) Creates weibull distribution with the given shape, scale and inverse cumulative probability accuracy and a location equal to zero.- Parameters:
alpha
- the shape parameter.beta
- the scale parameter.inverseCumAccuracy
- the maximum absolute error in inverse cumulative probability estimates (defaults toDEFAULT_INVERSE_ABSOLUTE_ACCURACY
)- Since:
- 2.1
-
-
Method Details
-
cumulativeProbability
public double cumulativeProbability(double x) For this distribution, X, this method returns P(X <x
).- Specified by:
cumulativeProbability
in interfaceDistribution
- Parameters:
x
- the value at which the CDF is evaluated.- Returns:
- CDF evaluated at
x
.
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getShape
public double getShape()Access the shape parameter.- Specified by:
getShape
in interfaceWeibullDistribution
- Returns:
- the shape parameter.
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getScale
public double getScale()Access the scale parameter.- Specified by:
getScale
in interfaceWeibullDistribution
- Returns:
- the scale parameter.
-
density
public double density(double x) Returns the probability density for a particular point.- Overrides:
density
in classAbstractContinuousDistribution
- Parameters:
x
- The point at which the density should be computed.- Returns:
- The pdf at point x.
- Since:
- 2.1
-
inverseCumulativeProbability
public double inverseCumulativeProbability(double p) For this distribution, X, this method returns the critical point x, such that P(X < x) =p
.Returns
Double.NEGATIVE_INFINITY
for p=0 andDouble.POSITIVE_INFINITY
for p=1.- Specified by:
inverseCumulativeProbability
in interfaceContinuousDistribution
- Overrides:
inverseCumulativeProbability
in classAbstractContinuousDistribution
- Parameters:
p
- the desired probability- Returns:
- x, such that P(X < x) =
p
- Throws:
IllegalArgumentException
- ifp
is not a valid probability.
-
setShape
Deprecated.as of 2.1 (class will become immutable in 3.0)Modify the shape parameter.- Specified by:
setShape
in interfaceWeibullDistribution
- Parameters:
alpha
- the new shape parameter value.
-
setScale
Deprecated.as of 2.1 (class will become immutable in 3.0)Modify the scale parameter.- Specified by:
setScale
in interfaceWeibullDistribution
- Parameters:
beta
- the new scale parameter value.
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getDomainLowerBound
protected double getDomainLowerBound(double p) Access the domain value lower bound, based onp
, used to bracket a CDF root. This method is used byinverseCumulativeProbability(double)
to find critical values.- Specified by:
getDomainLowerBound
in classAbstractContinuousDistribution
- Parameters:
p
- the desired probability for the critical value- Returns:
- domain value lower bound, i.e.
P(X < lower bound) <
p
-
getDomainUpperBound
protected double getDomainUpperBound(double p) Access the domain value upper bound, based onp
, used to bracket a CDF root. This method is used byinverseCumulativeProbability(double)
to find critical values.- Specified by:
getDomainUpperBound
in classAbstractContinuousDistribution
- Parameters:
p
- the desired probability for the critical value- Returns:
- domain value upper bound, i.e.
P(X < upper bound) >
p
-
getInitialDomain
protected double getInitialDomain(double p) Access the initial domain value, based onp
, used to bracket a CDF root. This method is used byinverseCumulativeProbability(double)
to find critical values.- Specified by:
getInitialDomain
in classAbstractContinuousDistribution
- Parameters:
p
- the desired probability for the critical value- Returns:
- initial domain value
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getSolverAbsoluteAccuracy
protected double getSolverAbsoluteAccuracy()Return the absolute accuracy setting of the solver used to estimate inverse cumulative probabilities.- Overrides:
getSolverAbsoluteAccuracy
in classAbstractContinuousDistribution
- Returns:
- the solver absolute accuracy
- Since:
- 2.1
-
getSupportLowerBound
public double getSupportLowerBound()Returns the lower bound of the support for the distribution. The lower bound of the support is always 0 no matter the parameters.- Returns:
- lower bound of the support (always 0)
- Since:
- 2.2
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getSupportUpperBound
public double getSupportUpperBound()Returns the upper bound of the support for the distribution. The upper bound of the support is always positive infinity no matter the parameters.- Returns:
- upper bound of the support (always Double.POSITIVE_INFINITY)
- Since:
- 2.2
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calculateNumericalMean
protected double calculateNumericalMean()Calculates the mean. The mean isscale * Gamma(1 + (1 / shape))
whereGamma(...)
is the Gamma-function- Returns:
- the mean
- Since:
- 2.2
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getNumericalMean
public double getNumericalMean()Returns the mean of the distribution.- Returns:
- the mean or Double.NaN if it's not defined
- Since:
- 2.2
-
getNumericalVariance
public double getNumericalVariance()Returns the variance of the distribution.- Returns:
- the variance (possibly Double.POSITIVE_INFINITY as
for certain cases in
TDistributionImpl
) or Double.NaN if it's not defined - Since:
- 2.2
-