gov.sandia.cognition.statistics.method

Class FriedmanConfidence.Statistic

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.method.AbstractConfidenceStatistic

gov.sandia.cognition.statistics.method.FriedmanConfidence.Statistic

All Implemented Interfaces:

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

Enclosing class:

FriedmanConfidence

public static class FriedmanConfidence.Statistic
extends AbstractConfidenceStatistic

Confidence statistic associated with the Friedman test using the tighter F-statistic.

See Also:

Serialized Form

Field Summary

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

nullHypothesisProbability

Constructor Summary

Constructors

Modifier	Constructor and Description
	Statistic(int treatmentCount, int subjectCount, java.util.ArrayList<java.lang.Double> treatmentRankMeans) Creates a new instance of Statistic
protected	Statistic(int treatmentCount, int subjectCount, java.util.ArrayList<java.lang.Double> treatmentRankMeans, double chiSquare) Creates a new instance of Statistic
protected	Statistic(int treatmentCount, int subjectCount, java.util.ArrayList<java.lang.Double> treatmentRankMeans, double chiSquare, double F) Creates a new instance of Statistic

Method Summary

Modifier and Type	Method and Description
FriedmanConfidence.Statistic	clone() This makes public the clone method on the Object class and removes the exception that it throws.
protected static double	computeChiSquare(int treatmentCount, int subjectCount, java.util.ArrayList<java.lang.Double> treatmentRankMeans) Computes the chi-square error for the rank means
double	getChiSquare() Getter for chiSquare
double	getChiSquareNullHypothesisProbability() Getter for chiSquareNullHypothesisProbability
double	getDegreesOfFreedom() Getter for degreesOfFreedom
double	getF() Getter for F.
int	getSubjectCount() Getter for subjectCount
double	getTestStatistic() Gets the statistic from which we compute the null-hypothesis probability.
int	getTreatmentCount() Getter for treatmentCount
java.util.ArrayList<java.lang.Double>	getTreatmentRankMeans() Getter for treatmentRankMeans

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

getNullHypothesisProbability, setNullHypothesisProbability, toString

Methods inherited from class java.lang.Object

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

Constructor Detail

Statistic

public Statistic(int treatmentCount,
                 int subjectCount,
                 java.util.ArrayList<java.lang.Double> treatmentRankMeans)

Creates a new instance of Statistic

Parameters:

treatmentCount - Number of treatments in the experiment

subjectCount - Number of subjects in the experiment

treatmentRankMeans - Mean rank for each treatment

Statistic

protected Statistic(int treatmentCount,
                    int subjectCount,
                    java.util.ArrayList<java.lang.Double> treatmentRankMeans,
                    double chiSquare)

Creates a new instance of Statistic

Parameters:

treatmentCount - Number of treatments in the experiment

subjectCount - Number of subjects in the experiment

treatmentRankMeans - Mean rank for each treatment

chiSquare - Value of the chi-square error for the treatment ranks

Statistic

protected Statistic(int treatmentCount,
                    int subjectCount,
                    java.util.ArrayList<java.lang.Double> treatmentRankMeans,
                    double chiSquare,
                    double F)

Creates a new instance of Statistic

Parameters:

treatmentCount - Number of treatments in the experiment

subjectCount - Number of subjects in the experiment

treatmentRankMeans - Mean rank for each treatment

chiSquare - Value of the chi-square error for the treatment ranks

F - F-statistic for the corrected chi-square using Snedecor's F distribution

Method Detail

computeChiSquare

protected static double computeChiSquare(int treatmentCount,
                                         int subjectCount,
                                         java.util.ArrayList<java.lang.Double> treatmentRankMeans)

Computes the chi-square error for the rank means

Parameters:

treatmentCount - Number of treatments in the experiment

subjectCount - Number of subjects in the experiment

treatmentRankMeans - Mean rank for each treatment

Returns:

Value of the chi-square error for the treatment ranks

clone

public FriedmanConfidence.Statistic clone()

Description copied from class: AbstractCloneableSerializable

This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class AbstractCloneableSerializable

Returns:

A clone of this object.

getTreatmentCount

public int getTreatmentCount()

Getter for treatmentCount

Returns:

Number of treatments in the experiment

getSubjectCount

public int getSubjectCount()

Getter for subjectCount

Returns:

Number of subjects in the experiment

getChiSquare

public double getChiSquare()

Getter for chiSquare

Returns:

Value of the chi-square error for the treatment ranks

getTreatmentRankMeans

public java.util.ArrayList<java.lang.Double> getTreatmentRankMeans()

Getter for treatmentRankMeans

Returns:

Mean rank for each treatment

getDegreesOfFreedom

public double getDegreesOfFreedom()

Getter for degreesOfFreedom

Returns:

Degrees of freedom of the chi-square

getChiSquareNullHypothesisProbability

public double getChiSquareNullHypothesisProbability()

Getter for chiSquareNullHypothesisProbability

Returns:

Null-hypothesis using the chi-square statistic

getF

public double getF()

Getter for F.

Returns:

F-statistic for the corrected chi-square using Snedecor's F distribution

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.