Package de.uka.ipd.sdq.probfunction.math.apache.distribution

Class 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:

  • 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 Details

    • 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