GaussianReflectionKernelDistribution (StochasticPetriNets)

java.lang.Object
- org.apache.commons.math3.distribution.AbstractRealDistribution
- - org.processmining.plugins.stochasticpetrinet.distribution.AnotherAbstractRealDistribution
  - - org.processmining.plugins.stochasticpetrinet.distribution.GaussianKernelDistribution
    - - org.processmining.plugins.stochasticpetrinet.distribution.GaussianReflectionKernelDistribution

All Implemented Interfaces:

java.io.Serializable, org.apache.commons.math3.analysis.UnivariateFunction, org.apache.commons.math3.distribution.RealDistribution

Direct Known Subclasses:

MeanCorrectedReflectionKernelDistribution
```
public class GaussianReflectionKernelDistribution
extends GaussianKernelDistribution
```
Very plain boundary reflection kernel estimator.

Author:

Andreas Rogge-Solti

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type Field Description

protected double threshold
The lower threshold where reflection occurs
- Fields inherited from class org.processmining.plugins.stochasticpetrinet.distribution.GaussianKernelDistribution
  h, kernelPointsAndWeights, ndist, NUMBER_OF_BINS, precision, sampleValues, veryPrecise
- Fields inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution
  random, randomData, SOLVER_DEFAULT_ABSOLUTE_ACCURACY

Constructor Summary

Constructors
Constructor	Description
`GaussianReflectionKernelDistribution()`	Boundary at x=0 for positive domain.
`GaussianReflectionKernelDistribution(double threshold)`
`GaussianReflectionKernelDistribution(double threshold, double precision)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`double`	`density(double x)`
`double`	`sample()`	Simply select one value from the observations at random and sample from it's Gaussian Kernel heap.

Methods inherited from class org.processmining.plugins.stochasticpetrinet.distribution.GaussianKernelDistribution
addValue, addValues, cumulativeProbability, cumulativeProbability, getDoubleArray, getH, getNumericalMean, getReasonableLowerBound, getReasonableUpperBound, getSupportLowerBound, getSupportUpperBound, getValues, isSupportConnected, isSupportLowerBoundInclusive, isSupportUpperBoundInclusive, probability, updateKernels, updateSmoothingParameter

Methods inherited from class org.processmining.plugins.stochasticpetrinet.distribution.AnotherAbstractRealDistribution
getNumericalVariance, value

Methods inherited from class org.apache.commons.math3.distribution.AbstractRealDistribution
getSolverAbsoluteAccuracy, inverseCumulativeProbability, logDensity, probability, reseedRandomGenerator, sample

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - threshold
```
protected double threshold
```
    The lower threshold where reflection occurs
- Constructor Detail
  - GaussianReflectionKernelDistribution
```
public GaussianReflectionKernelDistribution()
```
    Boundary at x=0 for positive domain.
  - GaussianReflectionKernelDistribution
```
public GaussianReflectionKernelDistribution(double threshold)
```
  - GaussianReflectionKernelDistribution
```
public GaussianReflectionKernelDistribution(double threshold,
                                            double precision)
```
- Method Detail
  - density
```
public double density(double x)
```
    Specified by:
    
    density in interface org.apache.commons.math3.distribution.RealDistribution
    
    Overrides:
    
    density in class GaussianKernelDistribution
  - sample
```
public double sample()
```
    Description copied from class: GaussianKernelDistribution
    
    Simply select one value from the observations at random and sample from it's Gaussian Kernel heap.
    
    Specified by:
    
    sample in interface org.apache.commons.math3.distribution.RealDistribution
    
    Overrides:
    
    sample in class GaussianKernelDistribution