gov.sandia.cognition.statistics.distribution

## Class KolmogorovDistribution

• ### Nested Class Summary

Nested Classes
Modifier and Type Class and Description
`static class ` `KolmogorovDistribution.CDF`
Contains the Cumulative Distribution Function description for the "D" statistic used within the Kolmogorov-Smirnov test.
• ### Field Summary

Fields
Modifier and Type Field and Description
`static double` `MEAN`
Value of the mean, found empirically, as I can't seem to find the answer in any reference I can get my hands on, 0.868481392844716.
`static double` `VARIANCE`
Value of the variance, found empirically, as I can't seem to find the answer in any reference I can get my hands on, 0.06759934611527044.
• ### Constructor Summary

Constructors
Constructor and Description
`KolmogorovDistribution()`
Creates a new instance of CumulativeDistribution
• ### Method Summary

All Methods
Modifier and Type Method and Description
`void` `convertFromVector(Vector parameters)`
Converts the object from a Vector of parameters.
`Vector` `convertToVector()`
Converts the object to a vector.
`KolmogorovDistribution.CDF` `getCDF()`
Gets the CDF of a scalar distribution.
`java.lang.Double` `getMaxSupport()`
Gets the minimum support (domain or input) of the distribution.
`java.lang.Double` `getMean()`
Gets the arithmetic mean, or "first central moment" or "expectation", of the distribution.
`double` `getMeanAsDouble()`
Gets the mean of the distribution as a double.
`java.lang.Double` `getMinSupport()`
Gets the minimum support (domain or input) of the distribution.
`double` `getVariance()`
Gets the variance of the distribution.
`void` ```sampleInto(java.util.Random random, int sampleCount, java.util.Collection<? super java.lang.Double> output)```
Draws multiple random samples from the distribution and puts the result into the given collection.
• ### Methods inherited from class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution

`clone`
• ### Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution

`sample, sample`
• ### Methods inherited from class java.lang.Object

`equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`
• ### Methods inherited from interface gov.sandia.cognition.statistics.Distribution

`sample, sample`
• ### Field Detail

• #### MEAN

`public static final double MEAN`
Value of the mean, found empirically, as I can't seem to find the answer in any reference I can get my hands on, 0.868481392844716.
Constant Field Values
• #### VARIANCE

`public static final double VARIANCE`
Value of the variance, found empirically, as I can't seem to find the answer in any reference I can get my hands on, 0.06759934611527044.
Constant Field Values
• ### Constructor Detail

• #### KolmogorovDistribution

`public KolmogorovDistribution()`
Creates a new instance of CumulativeDistribution
• ### Method Detail

• #### getMean

`public java.lang.Double getMean()`
Description copied from interface: `DistributionWithMean`
Gets the arithmetic mean, or "first central moment" or "expectation", of the distribution.
Returns:
Mean of the distribution.
• #### getMeanAsDouble

`public double getMeanAsDouble()`
Description copied from interface: `UnivariateDistribution`
Gets the mean of the distribution as a double.
Returns:
The mean as a double.
• #### sampleInto

```public void sampleInto(java.util.Random random,
int sampleCount,
java.util.Collection<? super java.lang.Double> output)```
Description copied from interface: `Distribution`
Draws multiple random samples from the distribution and puts the result into the given collection.
Parameters:
`random` - Random number generator to use.
`sampleCount` - The number of samples to draw. Cannot be negative.
`output` - The collection to add the samples into.
• #### getVariance

`public double getVariance()`
Description copied from interface: `UnivariateDistribution`
Gets the variance of the distribution. This is sometimes called the second central moment by more pedantic people, which is equivalent to the square of the standard deviation.
Returns:
Variance of the distribution.
• #### getCDF

`public KolmogorovDistribution.CDF getCDF()`
Description copied from interface: `UnivariateDistribution`
Gets the CDF of a scalar distribution.
Returns:
CDF of the scalar distribution.
• #### convertToVector

`public Vector convertToVector()`
Description copied from interface: `Vectorizable`
Converts the object to a vector.
Returns:
The Vector form of the object.
• #### convertFromVector

`public void convertFromVector(Vector parameters)`
Description copied from interface: `Vectorizable`
Converts the object from a Vector of parameters.
Parameters:
`parameters` - The parameters to incorporate.
• #### getMinSupport

`public java.lang.Double getMinSupport()`
Description copied from interface: `UnivariateDistribution`
Gets the minimum support (domain or input) of the distribution.
Returns:
Minimum support.
• #### getMaxSupport

`public java.lang.Double getMaxSupport()`
Description copied from interface: `UnivariateDistribution`
Gets the minimum support (domain or input) of the distribution.
Returns:
Minimum support.