javanpst.tests.goodness.K_STest

Class K_STest

java.lang.Object

javanpst.tests.StatisticalTest

javanpst.tests.goodness.K_STest.K_STest

public class K_STest
extends StatisticalTest

The K_S test. The Kolmogorov-Smirnov test for one sample can be used to adjust a given sample to a continuous distribution This version allows to adjust to several distributions , (Normal, Exponential, Uniform, Chi-Square, Laplace, Logistic, Gamma and Weibull) but they have to be completely defined

Constructor Summary

Constructors

Constructor and Description
K_STest() Default builder
K_STest(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(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(double m, double s) Sets adjustment to a Normal distribution, specifying mean and sigma.
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	getDn() Get Dn 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.

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

K_STest

public K_STest()

Default builder

K_STest

public K_STest(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(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(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

getDn

public double getDn()

Get Dn statistic

Returns:

Dn 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