javanpst.tests.goodness.A_DTest

Class A_DTest

java.lang.Object

javanpst.tests.StatisticalTest

javanpst.tests.goodness.A_DTest.A_DTest

public class A_DTest
extends StatisticalTest

The A_D test. The Anderson-Darling test can be used to adjust a given sample to either a Normal or a Exponential distribution. It is possible to select which parameters are defined for each distribution: Mean, sigma, both, or none. Additionally, adjust to other continuous distributions is supported, (Uniform, Chi-Square, Laplace, Logistic, Gamma and Weibull) but they have to be completely defined

Constructor Summary

Constructors

Constructor and Description
A_DTest() Default builder
A_DTest(NumericSequence newSequence) Builder.

Method Summary

Modifier and Type	Method and Description
void	adjustChiSquare(int freedom) Sets adjustment to a Chi-square distribution fully defined
void	adjustExponential() Sets adjustment to a Exponential distribution, without specifying mean.
void	adjustExponential(double m) Sets adjustment to a Exponential distribution fully defined
void	adjustGamma(double K, double lambda) Sets adjustment to a Gamma distribution fully defined
void	adjustLaplace(double mean, double scale) Sets adjustment to a Laplace distribution fully defined
void	adjustLogistic(double mean, double S) Sets adjustment to a Logistic distribution fully defined
void	adjustNormal() Sets adjustment to a Normal distribution, without specifying mean or sigma
void	adjustNormal(double m, double s) Sets adjustment to a Normal distribution, specifying mean and sigma.
void	adjustNormalMean(double m) Sets adjustment to a Normal distribution, specifying its mean.
void	adjustNormalVariance(double s) Sets adjustment to a Normal distribution, specifying its mean.
void	adjustUniform(double start, double end) Sets adjustment to a Uniform distribution fully defined
void	adjustWeibull(double K, double lambda) Sets adjustment to a Weibull distribution fully defined
void	clearData() Clears the data stored in the test
void	doTest() Performs the test
double	getA() Get A statistic
double	getPValue() Get p-value of the test
java.lang.String	printData() Prints the data stored in the test
java.lang.String	printReport() Prints a report with the results of the test
void	setData(NumericSequence newSequence) Load data to test.
double	W2() Get W2 statistic

Methods inherited from class javanpst.tests.StatisticalTest

isDataReady, isPerformed

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

A_DTest

public A_DTest()

Default builder

A_DTest

public A_DTest(NumericSequence newSequence)

Builder. Load data to test.

Parameters:

newSequence - data to test.

Method Detail

clearData

public void clearData()

Clears the data stored in the test

Specified by:

clearData in class StatisticalTest

setData

public void setData(NumericSequence newSequence)

Load data to test.

Parameters:

newSequence - data to test.

adjustNormal

public void adjustNormal()

Sets adjustment to a Normal distribution, without specifying mean or sigma

adjustNormalMean

public void adjustNormalMean(double m)

Sets adjustment to a Normal distribution, specifying its mean.

Parameters:

m - mean of the distribution

adjustNormalVariance

public void adjustNormalVariance(double s)

Sets adjustment to a Normal distribution, specifying its mean.

Parameters:

s - sigma parameter of the distribution

adjustNormal

public void adjustNormal(double m,
                         double s)

Sets adjustment to a Normal distribution, specifying mean and sigma.

Parameters:

m - mean of the distribution

s - sigma parameter of the distribution

adjustExponential

public void adjustExponential()

Sets adjustment to a Exponential distribution, without specifying mean.

adjustExponential

public void adjustExponential(double m)

Sets adjustment to a Exponential distribution fully defined

Parameters:

m - mean of the distribution

adjustUniform

public void adjustUniform(double start,
                          double end)

Sets adjustment to a Uniform distribution fully defined

Parameters:

start - lower limit of the distribution

end - upper limit of the distribution

adjustChiSquare

public void adjustChiSquare(int freedom)

Sets adjustment to a Chi-square distribution fully defined

Parameters:

freedom - number of degrees of freedom

adjustGamma

public void adjustGamma(double K,
                        double lambda)

Sets adjustment to a Gamma distribution fully defined

Parameters:

K - K parameter of the distribution

lambda - lambda parameter of the distribution

adjustLaplace

public void adjustLaplace(double mean,
                          double scale)

Sets adjustment to a Laplace distribution fully defined

Parameters:

mean - mean of the distribution

scale - scale parameter of the distribution

adjustLogistic

public void adjustLogistic(double mean,
                           double S)

Sets adjustment to a Logistic distribution fully defined

Parameters:

mean - mean of the distribution

S - S parameter of the distribution

adjustWeibull

public void adjustWeibull(double K,
                          double lambda)

Sets adjustment to a Weibull distribution fully defined

Parameters:

K - K parameter of the distribution

lambda - lambda parameter of the distribution

doTest

public void doTest()

Performs the test

Specified by:

doTest in class StatisticalTest

W2

public double W2()

Get W2 statistic

Returns:

W2 Statistic

getA

public double getA()

Get A statistic

Returns:

A Statistic

getPValue

public double getPValue()

Get p-value of the test

Returns:

p-value computed

printData

public java.lang.String printData()

Prints the data stored in the test

Specified by:

printData in class StatisticalTest

Returns:

Data stored

printReport

public java.lang.String printReport()

Prints a report with the results of the test

Specified by:

printReport in class StatisticalTest

Returns:

Output report