info.debatty.jinu.SummaryStatistics.java Source code

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Here is the source code for info.debatty.jinu.SummaryStatistics.java

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/*
 * The MIT License
 *
 * Copyright 2016 Thibault Debatty.
 *
 * 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 info.debatty.jinu;

import org.apache.commons.math3.distribution.TDistribution;
import org.apache.commons.math3.exception.MathIllegalArgumentException;

/**
 *
 * @author Thibault Debatty
 */
public class SummaryStatistics extends org.apache.commons.math3.stat.descriptive.SummaryStatistics {

    private static final double CONFIDENCE = 0.95;

    /**
     * Get the lower bound of confidence interval.
     * @return
     */
    public final double getMinInterval() {

        double ci = calcMeanCI(this, CONFIDENCE);
        return this.getMean() - ci;
    }

    /**
     *
     * @return
     */
    public final double getMaxInterval() {

        double ci = calcMeanCI(this, CONFIDENCE);
        return this.getMean() + ci;
    }

    private static double calcMeanCI(final SummaryStatistics stats, final double level) {

        try {
            // Create T Distribution with N-1 degrees of freedom
            TDistribution t_dist = new TDistribution(stats.getN() - 1);
            // Calculate critical value
            double crit_val = t_dist.inverseCumulativeProbability(1.0 - (1 - level) / 2);
            // Calculate confidence interval
            return crit_val * stats.getStandardDeviation() / Math.sqrt(stats.getN());
        } catch (MathIllegalArgumentException e) {
            return Double.NaN;
        }
    }

}