org.apache.commons.math.distribution
Class WeibullDistributionImpl

java.lang.Object
  extended by org.apache.commons.math.distribution.AbstractDistribution
      extended by org.apache.commons.math.distribution.AbstractContinuousDistribution
          extended by 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
See Also:
Serialized Form

Field Summary
static double DEFAULT_INVERSE_ABSOLUTE_ACCURACY
          Default inverse cumulative probability accuracy
 
Constructor Summary
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.
 
Method Summary
 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
 
Methods inherited from class org.apache.commons.math.distribution.AbstractDistribution
cumulativeProbability
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface org.apache.commons.math.distribution.Distribution
cumulativeProbability
 

Field Detail

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
Constructor Detail

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 to DEFAULT_INVERSE_ABSOLUTE_ACCURACY)
Since:
2.1
Method Detail

cumulativeProbability

public double cumulativeProbability(double x)
For this distribution, X, this method returns P(X < x).

Specified by:
cumulativeProbability in interface Distribution
Parameters:
x - the value at which the CDF is evaluated.
Returns:
CDF evaluated at x.

getShape

public double getShape()
Access the shape parameter.

Specified by:
getShape in interface WeibullDistribution
Returns:
the shape parameter.

getScale

public double getScale()
Access the scale parameter.

Specified by:
getScale in interface WeibullDistribution
Returns:
the scale parameter.

density

public double density(double x)
Returns the probability density for a particular point.

Overrides:
density in class AbstractContinuousDistribution
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 and Double.POSITIVE_INFINITY for p=1.

Specified by:
inverseCumulativeProbability in interface ContinuousDistribution
Overrides:
inverseCumulativeProbability in class AbstractContinuousDistribution
Parameters:
p - the desired probability
Returns:
x, such that P(X < x) = p
Throws:
IllegalArgumentException - if p is not a valid probability.

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 interface WeibullDistribution
Parameters:
alpha - the new shape parameter value.

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 interface WeibullDistribution
Parameters:
beta - the new scale parameter value.

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

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

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


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