gov.sandia.cognition.statistics.distribution
Class KolmogorovDistribution.CDF

java.lang.Object
  gov.sandia.cognition.util.AbstractCloneableSerializable
      gov.sandia.cognition.statistics.AbstractDistribution<NumberType>
          gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution<Double>
              gov.sandia.cognition.statistics.distribution.KolmogorovDistribution
                  gov.sandia.cognition.statistics.distribution.KolmogorovDistribution.CDF

All Implemented Interfaces:

Evaluator<Double,Double>, Vectorizable, ClosedFormCumulativeDistributionFunction<Double>, ClosedFormDistribution<Double>, ClosedFormUnivariateDistribution<Double>, CumulativeDistributionFunction<Double>, Distribution<Double>, DistributionWithMean<Double>, UnivariateDistribution<Double>, CloneableSerializable, Serializable, Cloneable

Enclosing class:

KolmogorovDistribution

public static class KolmogorovDistribution.CDF
extends KolmogorovDistribution
implements ClosedFormCumulativeDistributionFunction<Double>

Contains the Cumulative Distribution Function description for the "D" statistic used within the Kolmogorov-Smirnov test. This is taken from the probks() method from Numerical Recipes in C, p. 626.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution

KolmogorovDistribution.CDF

Field Summary

Fields inherited from class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution

MEAN, VARIANCE

Constructor Summary

KolmogorovDistribution.CDF()
Creates a new instance of CDF

Method Summary

static double	evaluate(double input) This is the probks() function from Numerical Recipes in C, pp.
Double	evaluate(Double input) Evaluates the function on the given input and returns the output.
KolmogorovDistribution.CDF	getCDF() Gets the CDF of a scalar distribution.

Methods inherited from class gov.sandia.cognition.statistics.distribution.KolmogorovDistribution

convertFromVector, convertToVector, getMaxSupport, getMean, getMinSupport, getVariance, sample

Methods inherited from class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution

clone

Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution

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.math.matrix.Vectorizable

clone, convertFromVector, convertToVector

Methods inherited from interface gov.sandia.cognition.statistics.UnivariateDistribution

getMaxSupport, getMinSupport, getVariance

Methods inherited from interface gov.sandia.cognition.statistics.DistributionWithMean

getMean

Methods inherited from interface gov.sandia.cognition.statistics.Distribution

sample, sample

Constructor Detail

KolmogorovDistribution.CDF

public KolmogorovDistribution.CDF()

Creates a new instance of CDF

Method Detail

evaluate

public Double evaluate(Double input)

Description copied from interface: Evaluator

Evaluates the function on the given input and returns the output.

Specified by:

evaluate in interface Evaluator<Double,Double>

Parameters:

input - The input to evaluate.

Returns:

The output produced by evaluating the input.

evaluate

@PublicationReference(author={"William H. Press","Saul A. Teukolsky","Willim T. Vetterling","Brian P. Flannery"},
                      title="Numerical Recipes in C, Second Edition",
                      type=Book,
                      year=1992,
                      pages=626,
                      notes={"Loosely based on the NRC probks() method.","Returns complement (1.0-value) of the NRC probks() method."},
                      url="http://www.nrbook.com/a/bookcpdf.php")
public static double evaluate(double input)

This is the probks() function from Numerical Recipes in C, pp. 626 The NR probks() function actually computes the complement to the CDF, so all the return values in this method will be 1.0-NR, when comparing the code to the NR code.

Parameters:

input - Value at which to evaluate the CDF

Returns:

CDF value at the input

getCDF

public KolmogorovDistribution.CDF getCDF()

Description copied from interface: UnivariateDistribution

Gets the CDF of a scalar distribution.

Specified by:

getCDF in interface ClosedFormUnivariateDistribution<Double>

Specified by:

getCDF in interface UnivariateDistribution<Double>

Overrides:

getCDF in class KolmogorovDistribution

Returns:

CDF of the scalar distribution.