Chi2.java

/***********************************************************************

	This file is part of KEEL-software, the Data Mining tool for regression, 
	classification, clustering, pattern mining and so on.

	Copyright (C) 2004-2010
	
	F. Herrera (herrera@decsai.ugr.es)
    L. S�nchez (luciano@uniovi.es)
    J. Alcal�-Fdez (jalcala@decsai.ugr.es)
    S. Garc�a (sglopez@ujaen.es)
    A. Fern�ndez (alberto.fernandez@ujaen.es)
    J. Luengo (julianlm@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 keel.Algorithms.Discretizers.MVD;


/**
 * <p>
 * This class implements the Chi2 table.
 * </p>
 */
public class Chi2 {
	
	final static double CHI_EPSILON=0.000001;
	final static double CHI_MAX=99999.0;
	final static double LOG_SQRT_PI=0.5723649429247000870717135;
	final static double I_SQRT_PI=0.5641895835477562869480795;
	final static double BIGX=20.0;
	
	final static double	Z_EPSILON=0.000001      ;
	final static double	Z_MAX=6.0   ;
	
	double poz_orig (double z)
	{
		double	y, x, w;
	
		if (z == 0.0)
			x = 0.0;
		else {
			y = 0.5 * Math.abs (z);
			if (y >= (Z_MAX * 0.5))
				x = 1.0;
			else if (y < 1.0) {
				w = y*y;
				x = ((((((((0.000124818987 * w
					-0.001075204047) * w +0.005198775019) * w
					-0.019198292004) * w +0.059054035642) * w
					-0.151968751364) * w +0.319152932694) * w
					-0.531923007300) * w +0.797884560593) * y * 2.0;
			} else {
				y -= 2.0;
				x = (((((((((((((-0.000045255659 * y
					+0.000152529290) * y -0.000019538132) * y
					-0.000676904986) * y +0.001390604284) * y
					-0.000794620820) * y -0.002034254874) * y
					+0.006549791214) * y -0.010557625006) * y
					+0.011630447319) * y -0.009279453341) * y
					+0.005353579108) * y -0.002141268741) * y
					+0.000535310849) * y +0.999936657524;
			}
		}
	
		return (z > 0.0 ? ((x + 1.0) * 0.5) : ((1.0 - x) * 0.5));
	}
	
	double ex(double x) {
		return (((x) < -BIGX) ? 0.0 : Math.exp (x));
	}

	double pochisq(double x, int df)
	{
		double a, y=0, s;
		double e, c, z;
		boolean even;		/* true if df is an even number */
	
		if (x <= 0.0 || df < 1)
			return (1.0);
	
		a = 0.5 * x;
		even = (2 * (df / 2)) == df;
		if (df > 1)
			y = ex(-a);
		s = (even ? y : (2.0 * poz_orig(-Math.sqrt(x))));
		if (df > 2) {
			x = 0.5 * (df - 1.0);
			z = (even ? 1.0 : 0.5);
			if (a > BIGX) {
				e = (even ? 0.0 : LOG_SQRT_PI);
				c = Math.log(a);
				while (z <= x) {
					e = Math.log(z) + e;
					s += ex(c * z - a - e);
					z += 1.0;
				}
				return (s);
			} else {
				e = (even ? 1.0 : (I_SQRT_PI / Math.sqrt(a)));
				c = 0.0;
				while (z <= x) {
					e = e * (a / z);
					c = c + e;
					z += 1.0;
				}
				return (c * y + s);
			}
		} else
		return (s);
	}

	/**
	 * This method obtains the p-value from a Chi square distribution
	 * @param p the distribution value
	 * @param df the degrees of freedom
	 * @return the associated p-value
	 */
	public double critchi (double p, int df) {
		double	minchisq = 0.0;
		double	maxchisq = CHI_MAX;
		double	chisqval;
		
		if (p <= 0.0)
			return (maxchisq);
		else if (p >= 1.0)
			return (0.0);
						
		chisqval = df / Math.sqrt (p);    /* fair first value */
		while (maxchisq - minchisq > CHI_EPSILON) {
			if (pochisq (chisqval, df) < p)
				maxchisq = chisqval;
			else
				minchisq = chisqval;
			chisqval = (maxchisq + minchisq) * 0.5;
		}
		return (chisqval);
	}

}