001/* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017package org.apache.commons.math3.stat.interval; 018 019import org.apache.commons.math3.distribution.FDistribution; 020 021/** 022 * Implements the Clopper-Pearson method for creating a binomial proportion confidence interval. 023 * 024 * @see <a 025 * href="http://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Clopper-Pearson_interval"> 026 * Clopper-Pearson interval (Wikipedia)</a> 027 * @since 3.3 028 */ 029public class ClopperPearsonInterval implements BinomialConfidenceInterval { 030 031 /** {@inheritDoc} */ 032 public ConfidenceInterval createInterval(int numberOfTrials, int numberOfSuccesses, 033 double confidenceLevel) { 034 IntervalUtils.checkParameters(numberOfTrials, numberOfSuccesses, confidenceLevel); 035 double lowerBound = 0; 036 double upperBound = 0; 037 final double alpha = (1.0 - confidenceLevel) / 2.0; 038 039 final FDistribution distributionLowerBound = new FDistribution(2 * (numberOfTrials - numberOfSuccesses + 1), 040 2 * numberOfSuccesses); 041 final double fValueLowerBound = distributionLowerBound.inverseCumulativeProbability(1 - alpha); 042 if (numberOfSuccesses > 0) { 043 lowerBound = numberOfSuccesses / 044 (numberOfSuccesses + (numberOfTrials - numberOfSuccesses + 1) * fValueLowerBound); 045 } 046 047 final FDistribution distributionUpperBound = new FDistribution(2 * (numberOfSuccesses + 1), 048 2 * (numberOfTrials - numberOfSuccesses)); 049 final double fValueUpperBound = distributionUpperBound.inverseCumulativeProbability(1 - alpha); 050 if (numberOfSuccesses > 0) { 051 upperBound = (numberOfSuccesses + 1) * fValueUpperBound / 052 (numberOfTrials - numberOfSuccesses + (numberOfSuccesses + 1) * fValueUpperBound); 053 } 054 055 return new ConfidenceInterval(lowerBound, upperBound, confidenceLevel); 056 } 057 058}