Interface MADDistributionEstimator<D extends Distribution>
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- Type Parameters:
D
- Distribution estimated.
- All Superinterfaces:
DistributionEstimator<D>
- All Known Implementing Classes:
CauchyMADEstimator
,ExponentialMADEstimator
,ExponentialMedianEstimator
,GumbelMADEstimator
,LaplaceMADEstimator
,LogisticMADEstimator
,NormalMADEstimator
,RayleighMADEstimator
,UniformMADEstimator
public interface MADDistributionEstimator<D extends Distribution> extends DistributionEstimator<D>
Distribuition estimators that use the method of moments (MOM), i.e. that only need the statistical moments of a data set.- Since:
- 0.6.0
- Author:
- Erich Schubert
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Method Summary
All Methods Static Methods Instance Methods Abstract Methods Default Methods Modifier and Type Method Description static double
computeMAD(double[] x, int len, double median)
Compute the median absolute deviation from median.static double
computeMAD(double[] data, int len, double median, double[] scratch)
Compute the median absolute deviation from median.default <A> D
estimate(A data, NumberArrayAdapter<?,A> adapter)
General form of the parameter estimationD
estimateFromMedianMAD(double median, double mad)
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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estimateFromMedianMAD
D estimateFromMedianMAD(double median, double mad)
General form of the parameter estimation- Parameters:
median
- Median valuemad
- Median absolute deviation from median- 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>
- Parameters:
data
- Data setadapter
- Number array adapter- Returns:
- Estimated distribution
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computeMAD
static double computeMAD(double[] data, int len, double median, double[] scratch)
Compute the median absolute deviation from median.- Parameters:
data
- Input datalen
- Length of input data to usemedian
- Median of input datascratch
- Scratch space, must be at least length len- Returns:
- MAD
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computeMAD
static double computeMAD(double[] x, int len, double median)
Compute the median absolute deviation from median.- Parameters:
x
- Input data will be modifiedlen
- Length where x is validmedian
- Median value.- Returns:
- Median absolute deviation from median.
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