Interface MeanVarianceDistributionEstimator<D extends Distribution>
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- Type Parameters:
D
- Distribution type
- All Superinterfaces:
DistributionEstimator<D>
,MOMDistributionEstimator<D>
- All Known Implementing Classes:
ExponentialMOMEstimator
,GammaMOMEstimator
,InverseGaussianMOMEstimator
,NormalMOMEstimator
public interface MeanVarianceDistributionEstimator<D extends Distribution> extends MOMDistributionEstimator<D>
Interface for estimators that only need mean and variance. These can implicitely (obviously) also handle full statistical moments.- Since:
- 0.6.0
- Author:
- Erich Schubert
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Method Summary
All Methods Instance Methods Abstract Methods Default Methods Modifier and Type Method Description default <A> D
estimate(A data, NumberArrayAdapter<?,A> adapter)
General form of the parameter estimationD
estimateFromMeanVariance(MeanVariance mv)
Estimate the distribution from mean and variance.default D
estimateFromStatisticalMoments(StatisticalMoments moments)
General form of the parameter estimation-
Methods inherited from interface elki.math.statistics.distribution.estimator.DistributionEstimator
estimate, getDistributionClass
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Method Detail
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estimateFromMeanVariance
D estimateFromMeanVariance(MeanVariance mv)
Estimate the distribution from mean and variance.- Parameters:
mv
- Mean and variance.- Returns:
- Distribution
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estimateFromStatisticalMoments
default D estimateFromStatisticalMoments(StatisticalMoments moments)
Description copied from interface:MOMDistributionEstimator
General form of the parameter estimation- Specified by:
estimateFromStatisticalMoments
in interfaceMOMDistributionEstimator<D extends Distribution>
- Parameters:
moments
- Statistical moments- Returns:
- Estimated distribution
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estimate
default <A> D estimate(A data, NumberArrayAdapter<?,A> adapter)
Description copied from interface:DistributionEstimator
General form of the parameter estimation- Specified by:
estimate
in interfaceDistributionEstimator<D extends Distribution>
- Specified by:
estimate
in interfaceMOMDistributionEstimator<D extends Distribution>
- Parameters:
data
- Data setadapter
- Number array adapter- Returns:
- Estimated distribution
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