/***********************************************************************
This file is part of JavaNPST, a Java library of NonParametric
Statistical Tests.
Copyright (C) 2011
J. Derrac (jderrac@decsai.ugr.es)
S. Garcia (sglopez@ujaen.es)
F. Herrera (herrera@decsai.ugr.es)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see http://www.gnu.org/licenses/
**********************************************************************/
package javanpst.distributions.tests;
import java.io.IOException;
import javax.xml.parsers.ParserConfigurationException;
import javax.xml.parsers.SAXParser;
import javax.xml.parsers.SAXParserFactory;
import org.xml.sax.SAXException;
import javanpst.distributions.DistributionDefinitions;
import javanpst.distributions.common.continuous.NormalDistribution;
import javanpst.data.distributions.incompleteTable.Incomplete2KeyTable;
import javanpst.data.readers.distributionReaders.RunsUpDownReaderFormat;
/**
* An implementation of the Runs up down distribution.
*
* Uses a Singleton pattern to ensure only an instance of the class is allowed.
*
* @author Joaqu�n Derrac Rus (jderrac@decsai.ugr.es)
* @version 1.0
*/
public class RunsUpDownDistribution extends TestDistribution{
/**
* Inner Normal distribution for approximated p-value
*/
private NormalDistribution normal;
/**
* Table of the distribution
*/
private static Incomplete2KeyTable table;
/**
* Critical values for the left tail
*/
private static double leftLimits [] = {0,0,0,1,1,2,3,3,4,5,5,6,7,7,8,9,9,10,11,11,12,13,13,14,15,15};
/**
* Private default builder.
*
* Initializes distribution tables
*/
private RunsUpDownDistribution(){
initialize();
}//end-method
/**
* Singleton pattern access to the distribution
*
* @return the instance of the distribution
*/
public static RunsUpDownDistribution getInstance(){
return SingletonHolder.distribution;
}//end-method
/**
* Singleton holder for the only instance of the distribution
*
* SingletonHolder is loaded on the first execution of getInstance()
* or the first access to SingletonHolder.distribution, not before.
*/
private static class SingletonHolder {
public static final RunsUpDownDistribution distribution = new RunsUpDownDistribution();
}//end-method
/**
* Generate distribution tables
*/
protected void generateTables(){
table = new Incomplete2KeyTable(26,25);
loadFiles();
normal= new NormalDistribution();
}//end-method
/**
* Load data files to fill distribution tables
*/
protected void loadFiles(){
try{
SAXParserFactory spf=SAXParserFactory.newInstance();
SAXParser sp = spf.newSAXParser();
sp.parse(this.getClass().getResourceAsStream("/tables/RunsUpDown/RunsUpDown.xml"), new RunsUpDownReaderFormat());
}catch(ParserConfigurationException e){
System.err.println("Parser error");
}catch(SAXException e2){
System.err.println("SAX error: " + e2.getStackTrace());
} catch (IOException e3) {
System.err.println("Input/Output error: " + e3.getMessage() );
}
}//end-method
/**
* Gets the table of the distribution
*
* @return Reference to the table
*/
public static Incomplete2KeyTable getTable(){
return table;
}//end-method
/**
* Computes exact p-value of the Runs up down distribution
*
* @param n number of elements
* @param R Runs up down statistic
* @param leftTail true if computing p-value of the left tail, false if right tail
* @return p-value computed
*/
public double computeExactProbability(int n,int R, boolean leftTail){
double value;
if((n<3)||(n>25)||(R>=n)||(R<1)){
return DistributionDefinitions.UNDEFINED;
}
if(leftTail){
if(R>leftLimits[n]){
return DistributionDefinitions.ALL;
}
}
else{
if(R<=leftLimits[n]){
return DistributionDefinitions.ALL;
}
}
value=table.get(n, R);
return value;
}//end-method
/**
* Computes asymptotic left tail p-value of the Runs Up Down distribution
*
* @param n number of elements in the sequence
* @param R total number of runs
* @return p-value computed
*/
public double computeAsymptoticLeftTailProbability(int n, int R){
double numerator,denominator,z;
denominator=Math.sqrt(((16.0*n)-29.0)/90.0);
numerator=R+0.5-(((2.0*n) - 1.0)/3.0);
z=numerator/denominator;
return normal.getTipifiedProbability(z, false);
}//end-method
/**
* Computes asymptotic left tail p-value of the Runs Up Down distribution
*
* @param n number of elements in the sequence
* @param R total number of runs
* @return p-value computed
*/
public double computeAsymptoticRightTailProbability(int n, int R){
double numerator,denominator,z;
denominator=Math.sqrt(((16.0*n)-29.0)/90.0);
numerator=R-0.5-(((2.0*n) - 1.0)/3.0);
z=numerator/denominator;
return normal.getTipifiedProbability(z, false);
}//end-method
/**
* Computes asymptotic double tail p-value of the Runs Up Down distribution
*
* @param n number of elements in the sequence
* @param R total number of runs
* @return p-value computed
*/
public double computeAsymptoticDoubleTailProbability(int n, int R){
double numerator,denominator,z;
double leftPValue,rightPValue;
denominator=Math.sqrt(((16.0*n)-29.0)/90.0);
numerator=R-0.5-(((2.0*n) - 1.0)/3.0);
z=numerator/denominator;
rightPValue=normal.getTipifiedProbability(z, false);
numerator=R+0.5-(((2.0*n) - 1.0)/3.0);
z=numerator/denominator;
normal.getTipifiedProbability(z, false);
leftPValue=normal.getTipifiedProbability(z, false);
return Math.min(Math.min(leftPValue,rightPValue)*2.0, 1.0);
}//end-method
}//end-class
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