ch.unil.genescore.vegas.DistributionMethods.java Source code

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Here is the source code for ch.unil.genescore.vegas.DistributionMethods.java

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/*******************************************************************************
 * Copyright (c) 2015 David Lamparter, Daniel Marbach
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in
 * all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 * THE SOFTWARE.
 *******************************************************************************/
package ch.unil.genescore.vegas;

import org.apache.commons.math3.distribution.ChiSquaredDistribution;
import org.apache.commons.math3.distribution.NormalDistribution;

public class DistributionMethods {

    private static ChiSquaredDistribution chiSquared1df_ = new ChiSquaredDistribution(1);
    private static NormalDistribution normalDist_ = new NormalDistribution();

    public static double chiSquared1dfCumulativeProbabilityUpperTail(double q) {
        double p;
        if (q > 50) {
            double q2 = Math.sqrt(q);
            p = normalCumulativeProbabilityUpperTailApprox(q2) * 2;
        } else {
            p = 1 - chiSquared1df_.cumulativeProbability(q);
        }
        return (p);
    }

    public static double chiSquared1dfInverseCumulativeProbabilityUpperTail(double p) {

        double p2 = p / 2;
        double q;
        if (p2 < 1E-14) {
            double upper = normalInversionUpperTailApprox(p2);
            q = Math.pow(upper, 2);

        } else {
            q = chiSquared1df_.inverseCumulativeProbability(1 - p);
        }
        return (q);

    }

    public static double normalCumulativeProbability(double q) {
        double p;
        if (q < -8) {
            double upper = normalCumulativeProbabilityUpperTailApprox(q);
            p = upper;

        } else {
            p = normalDist_.cumulativeProbability(q);
        }
        return (p);
    }

    public static double normalCumulativeProbabilityUpperTailApprox(double q) {

        q = Math.abs(q);
        double aa = -(q * q) / 2 - Math.log(q) - 0.5 * Math.log(2 * Math.PI);
        return (Math.exp(aa));
    }

    public static double normalInverseCumulativeProbability(double p) {
        double q;
        if (p < 10E-14) {
            double upper = normalInversionUpperTailApprox(p);
            q = (-1) * upper;

        } else {
            q = normalDist_.inverseCumulativeProbability(p);
        }
        return (q);
    }

    public static double normalInversionUpperTailApprox(double p) {
        // approximates tail integral of normal distribution function:: only use for very low values; below 10^-14
        double lp = Math.log(p);
        double diff = 1;
        double a1 = 1;
        double a = 1;
        while (diff > 0.001) {

            a = Math.sqrt((-lp - Math.log(Math.sqrt(2 * Math.PI)) - Math.log(a1)) * 2);
            diff = Math.abs(a - a1);
            a1 = a;

        }
        return (a);
    }

}