1 /* 2 * Licensed to the Apache Software Foundation (ASF) under one or more 3 * contributor license agreements. See the NOTICE file distributed with 4 * this work for additional information regarding copyright ownership. 5 * The ASF licenses this file to You under the Apache License, Version 2.0 6 * (the "License"); you may not use this file except in compliance with 7 * the License. You may obtain a copy of the License at 8 * 9 * http://www.apache.org/licenses/LICENSE-2.0 10 * 11 * Unless required by applicable law or agreed to in writing, software 12 * distributed under the License is distributed on an "AS IS" BASIS, 13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 14 * See the License for the specific language governing permissions and 15 * limitations under the License. 16 */ 17 package org.apache.commons.math4.legacy.stat.interval; 18 19 import org.apache.commons.math4.legacy.exception.NotPositiveException; 20 import org.apache.commons.math4.legacy.exception.NotStrictlyPositiveException; 21 import org.apache.commons.math4.legacy.exception.NumberIsTooLargeException; 22 import org.apache.commons.math4.legacy.exception.OutOfRangeException; 23 import org.apache.commons.math4.legacy.exception.util.LocalizedFormats; 24 25 /** 26 * Factory methods to generate confidence intervals for a binomial proportion. 27 * The supported methods are: 28 * <ul> 29 * <li>Agresti-Coull interval</li> 30 * <li>Clopper-Pearson method (exact method)</li> 31 * <li>Normal approximation (based on central limit theorem)</li> 32 * <li>Wilson score interval</li> 33 * </ul> 34 * 35 * @since 3.3 36 */ 37 public final class IntervalUtils { 38 39 /** Singleton Agresti-Coull instance. */ 40 private static final BinomialConfidenceInterval AGRESTI_COULL = new AgrestiCoullInterval(); 41 42 /** Singleton Clopper-Pearson instance. */ 43 private static final BinomialConfidenceInterval CLOPPER_PEARSON = new ClopperPearsonInterval(); 44 45 /** Singleton NormalApproximation instance. */ 46 private static final BinomialConfidenceInterval NORMAL_APPROXIMATION = new NormalApproximationInterval(); 47 48 /** Singleton Wilson score instance. */ 49 private static final BinomialConfidenceInterval WILSON_SCORE = new WilsonScoreInterval(); 50 51 /** 52 * Prevent instantiation. 53 */ 54 private IntervalUtils() { 55 } 56 57 /** 58 * Create an Agresti-Coull binomial confidence interval for the true 59 * probability of success of an unknown binomial distribution with the given 60 * observed number of trials, successes and confidence level. 61 * 62 * @param numberOfTrials number of trials 63 * @param numberOfSuccesses number of successes 64 * @param confidenceLevel desired probability that the true probability of 65 * success falls within the returned interval 66 * @return Confidence interval containing the probability of success with 67 * probability {@code confidenceLevel} 68 * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}. 69 * @throws NotPositiveException if {@code numberOfSuccesses < 0}. 70 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}. 71 * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}. 72 */ 73 public static ConfidenceInterval getAgrestiCoullInterval(int numberOfTrials, int numberOfSuccesses, 74 double confidenceLevel) { 75 return AGRESTI_COULL.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel); 76 } 77 78 /** 79 * Create a Clopper-Pearson binomial confidence interval for the true 80 * probability of success of an unknown binomial distribution with the given 81 * observed number of trials, successes and confidence level. 82 * <p> 83 * Preconditions: 84 * <ul> 85 * <li>{@code numberOfTrials} must be positive</li> 86 * <li>{@code numberOfSuccesses} may not exceed {@code numberOfTrials}</li> 87 * <li>{@code confidenceLevel} must be strictly between 0 and 1 (exclusive)</li> 88 * </ul> 89 * 90 * @param numberOfTrials number of trials 91 * @param numberOfSuccesses number of successes 92 * @param confidenceLevel desired probability that the true probability of 93 * success falls within the returned interval 94 * @return Confidence interval containing the probability of success with 95 * probability {@code confidenceLevel} 96 * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}. 97 * @throws NotPositiveException if {@code numberOfSuccesses < 0}. 98 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}. 99 * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}. 100 */ 101 public static ConfidenceInterval getClopperPearsonInterval(int numberOfTrials, int numberOfSuccesses, 102 double confidenceLevel) { 103 return CLOPPER_PEARSON.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel); 104 } 105 106 /** 107 * Create a binomial confidence interval for the true probability of success 108 * of an unknown binomial distribution with the given observed number of 109 * trials, successes and confidence level using the Normal approximation to 110 * the binomial distribution. 111 * 112 * @param numberOfTrials number of trials 113 * @param numberOfSuccesses number of successes 114 * @param confidenceLevel desired probability that the true probability of 115 * success falls within the interval 116 * @return Confidence interval containing the probability of success with 117 * probability {@code confidenceLevel} 118 */ 119 public static ConfidenceInterval getNormalApproximationInterval(int numberOfTrials, int numberOfSuccesses, 120 double confidenceLevel) { 121 return NORMAL_APPROXIMATION.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel); 122 } 123 124 /** 125 * Create a Wilson score binomial confidence interval for the true 126 * probability of success of an unknown binomial distribution with the given 127 * observed number of trials, successes and confidence level. 128 * 129 * @param numberOfTrials number of trials 130 * @param numberOfSuccesses number of successes 131 * @param confidenceLevel desired probability that the true probability of 132 * success falls within the returned interval 133 * @return Confidence interval containing the probability of success with 134 * probability {@code confidenceLevel} 135 * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}. 136 * @throws NotPositiveException if {@code numberOfSuccesses < 0}. 137 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}. 138 * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}. 139 */ 140 public static ConfidenceInterval getWilsonScoreInterval(int numberOfTrials, int numberOfSuccesses, 141 double confidenceLevel) { 142 return WILSON_SCORE.createInterval(numberOfTrials, numberOfSuccesses, confidenceLevel); 143 } 144 145 /** 146 * Verifies that parameters satisfy preconditions. 147 * 148 * @param numberOfTrials number of trials (must be positive) 149 * @param numberOfSuccesses number of successes (must not exceed numberOfTrials) 150 * @param confidenceLevel confidence level (must be strictly between 0 and 1) 151 * @throws NotStrictlyPositiveException if {@code numberOfTrials <= 0}. 152 * @throws NotPositiveException if {@code numberOfSuccesses < 0}. 153 * @throws NumberIsTooLargeException if {@code numberOfSuccesses > numberOfTrials}. 154 * @throws OutOfRangeException if {@code confidenceLevel} is not in the interval {@code (0, 1)}. 155 */ 156 static void checkParameters(int numberOfTrials, int numberOfSuccesses, double confidenceLevel) { 157 if (numberOfTrials <= 0) { 158 throw new NotStrictlyPositiveException(LocalizedFormats.NUMBER_OF_TRIALS, numberOfTrials); 159 } 160 if (numberOfSuccesses < 0) { 161 throw new NotPositiveException(LocalizedFormats.NEGATIVE_NUMBER_OF_SUCCESSES, numberOfSuccesses); 162 } 163 if (numberOfSuccesses > numberOfTrials) { 164 throw new NumberIsTooLargeException(LocalizedFormats.NUMBER_OF_SUCCESS_LARGER_THAN_POPULATION_SIZE, 165 numberOfSuccesses, numberOfTrials, true); 166 } 167 if (confidenceLevel <= 0 || confidenceLevel >= 1) { 168 throw new OutOfRangeException(LocalizedFormats.OUT_OF_BOUNDS_CONFIDENCE_LEVEL, 169 confidenceLevel, 0, 1); 170 } 171 } 172 }