1 | /*
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2 | * Licensed to the Apache Software Foundation (ASF) under one or more
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3 | * contributor license agreements. See the NOTICE file distributed with
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4 | * this work for additional information regarding copyright ownership.
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5 | * The ASF licenses this file to You under the Apache License, Version 2.0
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6 | * (the "License"); you may not use this file except in compliance with
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7 | * the License. You may obtain a copy of the License at
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8 | *
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9 | * http://www.apache.org/licenses/LICENSE-2.0
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10 | *
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11 | * Unless required by applicable law or agreed to in writing, software
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12 | * distributed under the License is distributed on an "AS IS" BASIS,
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13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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14 | * See the License for the specific language governing permissions and
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15 | * limitations under the License.
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16 | */
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17 | package agents.anac.y2019.harddealer.math3.stat.interval;
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18 |
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19 | import agents.anac.y2019.harddealer.math3.distribution.NormalDistribution;
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20 | import agents.anac.y2019.harddealer.math3.util.FastMath;
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21 |
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22 | /**
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23 | * Implements the Agresti-Coull method for creating a binomial proportion confidence interval.
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24 | *
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25 | * @see <a
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26 | * href="http://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Agresti-Coull_Interval">
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27 | * Agresti-Coull interval (Wikipedia)</a>
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28 | * @since 3.3
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29 | */
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30 | public class AgrestiCoullInterval implements BinomialConfidenceInterval {
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31 |
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32 | /** {@inheritDoc} */
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33 | public ConfidenceInterval createInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel) {
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34 | IntervalUtils.checkParameters(numberOfTrials, numberOfSuccesses, confidenceLevel);
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35 | final double alpha = (1.0 - confidenceLevel) / 2;
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36 | final NormalDistribution normalDistribution = new NormalDistribution();
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37 | final double z = normalDistribution.inverseCumulativeProbability(1 - alpha);
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38 | final double zSquared = FastMath.pow(z, 2);
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39 | final double modifiedNumberOfTrials = numberOfTrials + zSquared;
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40 | final double modifiedSuccessesRatio = (1.0 / modifiedNumberOfTrials) * (numberOfSuccesses + 0.5 * zSquared);
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41 | final double difference = z *
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42 | FastMath.sqrt(1.0 / modifiedNumberOfTrials * modifiedSuccessesRatio *
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43 | (1 - modifiedSuccessesRatio));
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44 | return new ConfidenceInterval(modifiedSuccessesRatio - difference, modifiedSuccessesRatio + difference,
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45 | confidenceLevel);
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46 | }
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47 |
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48 | }
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