GammaDistributionFromMomentsImpl

java.lang.Object
- org.apache.commons.math.distribution.AbstractDistribution
- - org.apache.commons.math.distribution.AbstractContinuousDistribution
  - - org.apache.commons.math.distribution.GammaDistributionImpl
    - - de.uka.ipd.sdq.probfunction.math.apache.distribution.GammaDistributionFromMomentsImpl

All Implemented Interfaces:

Serializable, org.apache.commons.math.distribution.ContinuousDistribution, org.apache.commons.math.distribution.Distribution, org.apache.commons.math.distribution.GammaDistribution, org.apache.commons.math.distribution.HasDensity<Double>
```
public class GammaDistributionFromMomentsImpl
extends org.apache.commons.math.distribution.GammaDistributionImpl
```
SDQ implementation of GammaDistFromMoments based on apache.commons.math

See Also:

Serialized Form

Field Summary
- Fields inherited from class org.apache.commons.math.distribution.GammaDistributionImpl
  DEFAULT_INVERSE_ABSOLUTE_ACCURACY

Constructor Summary

Constructors
Constructor	Description
`GammaDistributionFromMomentsImpl(double mean, double variance)`	Create a new gamma distribution with the given mean and variance values.

Method Summary
- Methods inherited from class org.apache.commons.math.distribution.GammaDistributionImpl
  cumulativeProbability, density, density, getAlpha, getBeta, getDomainLowerBound, getDomainUpperBound, getInitialDomain, getSolverAbsoluteAccuracy, inverseCumulativeProbability, setAlpha, setBeta
- 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

- Constructor Detail
  - GammaDistributionFromMomentsImpl
```
public GammaDistributionFromMomentsImpl(double mean,
                                        double variance)
```
    Create a new gamma distribution with the given mean and variance values.
    
    Parameters:
    
    mean - The mean value
    
    variance - The variance value