home | career | drupal | java | mac | mysql | perl | scala | uml | unix  

Java example source code file (IntervalUtils.java)

This example Java source code file (IntervalUtils.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

agresti_coull, agresticoullinterval, binomialconfidenceinterval, clopper_pearson, clopperpearsoninterval, confidenceinterval, intervalutils, normal_approximation, normalapproximationinterval, wilson_score, wilsonscoreinterval

The IntervalUtils.java Java example source code

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.commons.math3.stat.interval;

import org.apache.commons.math3.exception.NotPositiveException;
import org.apache.commons.math3.exception.NotStrictlyPositiveException;
import org.apache.commons.math3.exception.NumberIsTooLargeException;
import org.apache.commons.math3.exception.OutOfRangeException;
import org.apache.commons.math3.exception.util.LocalizedFormats;

/**
 * Factory methods to generate confidence intervals for a binomial proportion.
 * The supported methods are:
 * <ul>
 * <li>Agresti-Coull interval
 * <li>Clopper-Pearson method (exact method)
 * <li>Normal approximation (based on central limit theorem)
 * <li>Wilson score interval
 * </ul>
 *
 * @since 3.3
 */
public final class IntervalUtils {

    /** Singleton Agresti-Coull instance. */
    private static final BinomialConfidenceInterval AGRESTI_COULL = new AgrestiCoullInterval();

    /** Singleton Clopper-Pearson instance. */
    private static final BinomialConfidenceInterval CLOPPER_PEARSON = new ClopperPearsonInterval();

    /** Singleton NormalApproximation instance. */
    private static final BinomialConfidenceInterval NORMAL_APPROXIMATION = new NormalApproximationInterval();

    /** Singleton Wilson score instance. */
    private static final BinomialConfidenceInterval WILSON_SCORE = new WilsonScoreInterval();

    /**
     * Prevent instantiation.
     */
    private IntervalUtils() {
    }

    /**
     * Create an Agresti-Coull binomial confidence interval for the true
     * probability of success of an unknown binomial distribution with the given
     * observed number of trials, successes and confidence level.
     *
     * @param numberOfTrials number of trials
     * @param numberOfSuccesses number of successes
     * @param confidenceLevel desired probability that the true probability of
     *        success falls within the returned interval
     * @return Confidence interval containing the probability of success with
     *         probability {@code confidenceLevel}
     * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}.
     * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
     * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}.
     * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}.
     */
    public static ConfidenceInterval getAgrestiCoullInterval(int numberOfTrials, int numberOfSuccesses,
                                                             double confidenceLevel) {
        return AGRESTI_COULL.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel);
    }

    /**
     * Create a Clopper-Pearson binomial confidence interval for the true
     * probability of success of an unknown binomial distribution with the given
     * observed number of trials, successes and confidence level.
     * <p>
     * Preconditions:
     * <ul>
     * <li>{@code numberOfTrials} must be positive
     * <li>{@code numberOfSuccesses} may not exceed {@code numberOfTrials}
     * <li>{@code confidenceLevel} must be strictly between 0 and 1 (exclusive)
     * </ul>
     * </p>
     *
     * @param numberOfTrials number of trials
     * @param numberOfSuccesses number of successes
     * @param confidenceLevel desired probability that the true probability of
     *        success falls within the returned interval
     * @return Confidence interval containing the probability of success with
     *         probability {@code confidenceLevel}
     * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}.
     * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
     * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}.
     * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}.
     */
    public static ConfidenceInterval getClopperPearsonInterval(int numberOfTrials, int numberOfSuccesses,
                                                               double confidenceLevel) {
        return CLOPPER_PEARSON.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel);
    }

    /**
     * Create a binomial confidence interval for the true probability of success
     * of an unknown binomial distribution with the given observed number of
     * trials, successes and confidence level using the Normal approximation to
     * the binomial distribution.
     *
     * @param numberOfTrials number of trials
     * @param numberOfSuccesses number of successes
     * @param confidenceLevel desired probability that the true probability of
     *        success falls within the interval
     * @return Confidence interval containing the probability of success with
     *         probability {@code confidenceLevel}
     */
    public static ConfidenceInterval getNormalApproximationInterval(int numberOfTrials, int numberOfSuccesses,
                                                                    double confidenceLevel) {
        return NORMAL_APPROXIMATION.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel);
    }

    /**
     * Create a Wilson score binomial confidence interval for the true
     * probability of success of an unknown binomial distribution with the given
     * observed number of trials, successes and confidence level.
     *
     * @param numberOfTrials number of trials
     * @param numberOfSuccesses number of successes
     * @param confidenceLevel desired probability that the true probability of
     *        success falls within the returned interval
     * @return Confidence interval containing the probability of success with
     *         probability {@code confidenceLevel}
     * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}.
     * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
     * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}.
     * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}.
     */
    public static ConfidenceInterval getWilsonScoreInterval(int numberOfTrials, int numberOfSuccesses,
                                                            double confidenceLevel) {
        return WILSON_SCORE.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel);
    }

    /**
     * Verifies that parameters satisfy preconditions.
     *
     * @param numberOfTrials number of trials (must be positive)
     * @param numberOfSuccesses number of successes (must not exceed numberOfTrials)
     * @param confidenceLevel confidence level (must be strictly between 0 and 1)
     * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}.
     * @throws NotPositiveException if {@code numberOfSuccesses < 0}.
     * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}.
     * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}.
     */
    static void checkParameters(int numberOfTrials, int numberOfSuccesses, double confidenceLevel) {
        if (numberOfTrials <= 0) {
            throw new NotStrictlyPositiveException(LocalizedFormats.NUMBER_OF_TRIALS, numberOfTrials);
        }
        if (numberOfSuccesses < 0) {
            throw new NotPositiveException(LocalizedFormats.NEGATIVE_NUMBER_OF_SUCCESSES, numberOfSuccesses);
        }
        if (numberOfSuccesses > numberOfTrials) {
            throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE,
                                                numberOfSuccesses, numberOfTrials, true);
        }
        if (confidenceLevel <= 0 || confidenceLevel >= 1) {
            throw new OutOfRangeException(LocalizedFormats.OUT_OF_BOUNDS_CONFIDENCE_LEVEL,
                                          confidenceLevel, 0, 1);
        }
    }

}

Other Java examples (source code examples)

Here is a short list of links related to this Java IntervalUtils.java source code file:



my book on functional programming

 

new blog posts

 

Copyright 1998-2019 Alvin Alexander, alvinalexander.com
All Rights Reserved.

A percentage of advertising revenue from
pages under the /java/jwarehouse URI on this website is
paid back to open source projects.