ClopperPearsonInterval.java

  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. import org.apache.commons.statistics.distribution.FDistribution;

  19. /**
  20.  * Implements the Clopper-Pearson method for creating a binomial proportion confidence interval.
  21.  *
  22.  * @see <a
  23.  *      href="http://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Clopper-Pearson_interval">
  24.  *      Clopper-Pearson interval (Wikipedia)</a>
  25.  * @since 3.3
  26.  */
  27. public class ClopperPearsonInterval implements BinomialConfidenceInterval {

  28.     /** {@inheritDoc} */
  29.     @Override
  30.     public ConfidenceInterval createInterval(int numberOfTrials,
  31.                                              int numberOfSuccesses,
  32.                                              double confidenceLevel) {
  33.         IntervalUtils.checkParameters(numberOfTrials, numberOfSuccesses, confidenceLevel);
  34.         double lowerBound = 0;
  35.         double upperBound = 1;

  36.         final double alpha = 0.5 * (1 - confidenceLevel);

  37.         if (numberOfSuccesses > 0) {
  38.             final FDistribution distributionLowerBound = FDistribution.of(2.0 * (numberOfTrials - numberOfSuccesses + 1),
  39.                                                                           2.0 * numberOfSuccesses);
  40.             final double fValueLowerBound = distributionLowerBound.inverseSurvivalProbability(alpha);
  41.             lowerBound = numberOfSuccesses /
  42.                 (numberOfSuccesses + (numberOfTrials - numberOfSuccesses + 1) * fValueLowerBound);
  43.         }

  44.         if (numberOfSuccesses < numberOfTrials) {
  45.             final FDistribution distributionUpperBound = FDistribution.of(2.0 * (numberOfSuccesses + 1),
  46.                                                                           2.0 * (numberOfTrials - numberOfSuccesses));
  47.             final double fValueUpperBound = distributionUpperBound.inverseSurvivalProbability(alpha);
  48.             upperBound = (numberOfSuccesses + 1) * fValueUpperBound /
  49.                 (numberOfTrials - numberOfSuccesses + (numberOfSuccesses + 1) * fValueUpperBound);
  50.         }

  51.         return new ConfidenceInterval(lowerBound, upperBound, confidenceLevel);
  52.     }
  53. }