gov.sandia.cognition.statistics.method

Class KolmogorovSmirnovConfidence.Statistic

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.method.AbstractConfidenceStatistic

gov.sandia.cognition.statistics.method.KolmogorovSmirnovConfidence.Statistic

All Implemented Interfaces:

ConfidenceStatistic, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

KolmogorovSmirnovConfidence

public static class KolmogorovSmirnovConfidence.Statistic
extends AbstractConfidenceStatistic

Computes the ConfidenceStatistic associated with a K-S test

See Also:

Serialized Form

Field Summary

Fields inherited from class gov.sandia.cognition.statistics.method.AbstractConfidenceStatistic

nullHypothesisProbability

Constructor Summary

Constructors

Constructor and Description
Statistic(double Ne, double D) Creates a new instance of Statistic

Method Summary

Modifier and Type	Method and Description
double	getD() Setter for D
double	getNe() Getter for Ne
double	getTestStatistic() Gets the statistic from which we compute the null-hypothesis probability.
static double	KSsignificance(double Ne, double D) Computes the significance of the K-S test from the given degrees of freedom and D-statistic.
protected void	setD(double D) Setter for D
protected void	setNe(double Ne) Setter for Ne

Methods inherited from class gov.sandia.cognition.statistics.method.AbstractConfidenceStatistic

getNullHypothesisProbability, setNullHypothesisProbability, toString

Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable

clone

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Constructor Detail

Statistic

public Statistic(double Ne,
                 double D)

Creates a new instance of Statistic

Parameters:

D - This is the D-statistic used in the K-S CDF, usually known as the D-statistic, which is the maximum difference between the two distributions. I use the two-tail version of D.

Ne - This is the degrees of freedom in the K-S distribution for the CDF calculation.

Method Detail

KSsignificance

@PublicationReference(author={"William H. Press","Saul A. Teukolsky","William T. Vetterling","Brian P. Flannery"},
                      title="Numerical Recipes in C, Second Edition",
                      type=Book,
                      year=1992,
                      pages=624,
                      notes={"Section 14.3","Equation 14.3.9"})
public static double KSsignificance(double Ne,
                                                                                                                                                                                                                                                                                                                                                                                                double D)

Computes the significance of the K-S test from the given degrees of freedom and D-statistic. This approximation is from Numerical Recipes in C, p. 624

Parameters:

Ne - Number of degrees of freedom in the data

D - This is the D-statistic used in the K-S CDF, usually known as the D-statistic, which is the maximum difference between the two distributions. I use the two-tail version of D.

Returns:

Probability of the null hypothesis

getD

public double getD()

Setter for D

Returns:

This is the D-statistic used in the K-S CDF, usually known as the D-statistic, which is the maximum difference between the two distributions. I use the two-tail version of D.

setD

protected void setD(double D)

Setter for D

Parameters:

D - This is the D-statistic used in the K-S CDF, usually known as the D-statistic, which is the maximum difference between the two distributions. I use the two-tail version of D. 0.0 <= D <= 1.0

getNe

public double getNe()

Getter for Ne

Returns:

This is the degrees of freedom in the K-S distribution for the CDF calculation.

setNe

protected void setNe(double Ne)

Setter for Ne

Parameters:

Ne - This is the degrees of freedom in the K-S distribution for the CDF calculation.

getTestStatistic

public double getTestStatistic()

Description copied from interface: ConfidenceStatistic

Gets the statistic from which we compute the null-hypothesis probability. In an ANOVA, this would be the "F" statistic. In a t-test, this would be the "t" value. And so forth.

Returns:

Confidence statistic used to compute the null-hypothesis probability.