Class WeibullDistributionImpl
- java.lang.Object
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- org.apache.commons.math.distribution.AbstractDistribution
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- org.apache.commons.math.distribution.AbstractContinuousDistribution
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- org.apache.commons.math.distribution.WeibullDistributionImpl
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- All Implemented Interfaces:
java.io.Serializable
,ContinuousDistribution
,Distribution
,WeibullDistribution
public class WeibullDistributionImpl extends AbstractContinuousDistribution implements WeibullDistribution, java.io.Serializable
Default implementation ofWeibullDistribution
.- Since:
- 1.1
- See Also:
- Serialized Form
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Field Summary
Fields Modifier and Type Field Description static double
DEFAULT_INVERSE_ABSOLUTE_ACCURACY
Default inverse cumulative probability accuracy
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Constructor Summary
Constructors Constructor Description WeibullDistributionImpl(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.
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Method Summary
All Methods Instance Methods Concrete Methods Deprecated Methods Modifier and Type Method Description 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.double
getNumericalMean()
Returns the mean of the distribution.double
getNumericalVariance()
Returns the variance of the distribution.double
getScale()
Access the scale parameter.double
getShape()
Access the shape parameter.double
getSupportLowerBound()
Returns the lower bound of the support for the distribution.double
getSupportUpperBound()
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
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Methods inherited from class org.apache.commons.math.distribution.AbstractDistribution
cumulativeProbability
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Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface org.apache.commons.math.distribution.Distribution
cumulativeProbability
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Field Detail
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DEFAULT_INVERSE_ABSOLUTE_ACCURACY
public static final double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
Default inverse cumulative probability accuracy- Since:
- 2.1
- See Also:
- Constant Field Values
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Constructor Detail
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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.
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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
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Method Detail
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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.
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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
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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:
java.lang.IllegalArgumentException
- ifp
is not a valid probability.
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setShape
@Deprecated public void setShape(double alpha)
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.
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setScale
@Deprecated public void setScale(double beta)
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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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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getNumericalMean
public double getNumericalMean()
Returns the mean of the distribution.- Returns:
- the mean or Double.NaN if it's not defined
- Since:
- 2.2
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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
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