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 agents.anac.y2019.harddealer.math3.stat.interval;
|
---|
18 |
|
---|
19 | import agents.anac.y2019.harddealer.math3.distribution.FDistribution;
|
---|
20 |
|
---|
21 | /**
|
---|
22 | * Implements the Clopper-Pearson method for creating a binomial proportion confidence interval.
|
---|
23 | *
|
---|
24 | * @see <a
|
---|
25 | * href="http://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Clopper-Pearson_interval">
|
---|
26 | * Clopper-Pearson interval (Wikipedia)</a>
|
---|
27 | * @since 3.3
|
---|
28 | */
|
---|
29 | public class ClopperPearsonInterval implements BinomialConfidenceInterval {
|
---|
30 |
|
---|
31 | /** {@inheritDoc} */
|
---|
32 | public ConfidenceInterval createInterval(int numberOfTrials, int numberOfSuccesses,
|
---|
33 | double confidenceLevel) {
|
---|
34 | IntervalUtils.checkParameters(numberOfTrials, numberOfSuccesses, confidenceLevel);
|
---|
35 | double lowerBound = 0;
|
---|
36 | double upperBound = 0;
|
---|
37 | final double alpha = (1.0 - confidenceLevel) / 2.0;
|
---|
38 |
|
---|
39 | final FDistribution distributionLowerBound = new FDistribution(2 * (numberOfTrials - numberOfSuccesses + 1),
|
---|
40 | 2 * numberOfSuccesses);
|
---|
41 | final double fValueLowerBound = distributionLowerBound.inverseCumulativeProbability(1 - alpha);
|
---|
42 | if (numberOfSuccesses > 0) {
|
---|
43 | lowerBound = numberOfSuccesses /
|
---|
44 | (numberOfSuccesses + (numberOfTrials - numberOfSuccesses + 1) * fValueLowerBound);
|
---|
45 | }
|
---|
46 |
|
---|
47 | final FDistribution distributionUpperBound = new FDistribution(2 * (numberOfSuccesses + 1),
|
---|
48 | 2 * (numberOfTrials - numberOfSuccesses));
|
---|
49 | final double fValueUpperBound = distributionUpperBound.inverseCumulativeProbability(1 - alpha);
|
---|
50 | if (numberOfSuccesses > 0) {
|
---|
51 | upperBound = (numberOfSuccesses + 1) * fValueUpperBound /
|
---|
52 | (numberOfTrials - numberOfSuccesses + (numberOfSuccesses + 1) * fValueUpperBound);
|
---|
53 | }
|
---|
54 |
|
---|
55 | return new ConfidenceInterval(lowerBound, upperBound, confidenceLevel);
|
---|
56 | }
|
---|
57 |
|
---|
58 | }
|
---|