StandardNormalSignificanceTest.java
package org.drip.sample.hypothesistest;
import org.drip.measure.gaussian.R1UnivariateNormal;
import org.drip.numerical.common.FormatUtil;
import org.drip.service.env.EnvManager;
import org.drip.validation.hypothesis.SignificanceTestSetting;
import org.drip.validation.evidence.Ensemble;
import org.drip.validation.evidence.Sample;
import org.drip.validation.evidence.TestStatisticEvaluator;
import org.drip.validation.hypothesis.SignificanceTestOutcome;
import org.drip.validation.hypothesis.ProbabilityIntegralTransformTest;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2019 Lakshmi Krishnamurthy
*
* This file is part of DROP, an open-source library targeting risk, transaction costs, exposure, margin
* calculations, and portfolio construction within and across fixed income, credit, commodity, equity,
* FX, and structured products.
*
* https://lakshmidrip.github.io/DROP/
*
* DROP is composed of three main modules:
*
* - DROP Analytics Core - https://lakshmidrip.github.io/DROP-Analytics-Core/
* - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
* - DROP Numerical Core - https://lakshmidrip.github.io/DROP-Numerical-Core/
*
* DROP Analytics Core implements libraries for the following:
* - Fixed Income Analytics
* - Asset Backed Analytics
* - XVA Analytics
* - Exposure and Margin Analytics
*
* DROP Portfolio Core implements libraries for the following:
* - Asset Allocation Analytics
* - Transaction Cost Analytics
*
* DROP Numerical Core implements libraries for the following:
* - Statistical Learning Library
* - Numerical Optimizer Library
* - Machine Learning Library
* - Spline Builder Library
*
* Documentation for DROP is Spread Over:
*
* - Main => https://lakshmidrip.github.io/DROP/
* - Wiki => https://github.com/lakshmiDRIP/DROP/wiki
* - GitHub => https://github.com/lakshmiDRIP/DROP
* - Javadoc => https://lakshmidrip.github.io/DROP/Javadoc/index.html
* - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
* - Release Versions => https://lakshmidrip.github.io/DROP/version.html
* - Community Credits => https://lakshmidrip.github.io/DROP/credits.html
* - Issues Catalog => https://github.com/lakshmiDRIP/DROP/issues
* - JUnit => https://lakshmidrip.github.io/DROP/junit/index.html
* - Jacoco => https://lakshmidrip.github.io/DROP/jacoco/index.html
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
*
* You may obtain a copy of the License at
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
*
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/**
* <i>StandardNormalSignificanceTest</i> illustrates Significance Test for a Standard Normal Ensemble.
*
* <br><br>
* <ul>
* <li>
* Bhattacharya, B., and D. Habtzghi (2002): Median of the p-value under the Alternate Hypothesis
* American Statistician 56 (3) 202-206
* </li>
* <li>
* Head, M. L., L. Holman, R, Lanfear, A. T. Kahn, and M. D. Jennions (2015): The Extent and
* Consequences of p-Hacking in Science PLoS Biology 13 (3) e1002106
* </li>
* <li>
* Wasserstein, R. L., and N. A. Lazar (2016): The ASA’s Statement on p-values: Context, Process,
* and Purpose American Statistician 70 (2) 129-133
* </li>
* <li>
* Wetzels, R., D. Matzke, M. D. Lee, J. N. Rouder, G, J, Iverson, and E. J. Wagenmakers (2011):
* Statistical Evidence in Experimental Psychology: An Empirical Comparison using 855 t-Tests
* Perspectives in Psychological Science 6 (3) 291-298
* </li>
* <li>
* Wikipedia (2019): p-value https://en.wikipedia.org/wiki/P-value
* </li>
* </ul>
*
* <br><br>
- * <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/AnalyticsCore.md">Analytics Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ModelValidationAnalyticsLibrary.md">Model Validation Analytics Library</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/validation">Model Validation Suite</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/validation/core">Core Model Validation Support Utilities</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class StandardNormalSignificanceTest
{
private static final double UnivariateRandom()
throws Exception
{
return R1UnivariateNormal.Standard().random();
}
private static final Sample GenerateSample (
final int drawCount)
throws Exception
{
double[] univariateRandomArray = new double[drawCount];
for (int drawIndex = 0; drawIndex < drawCount; ++drawIndex)
{
univariateRandomArray[drawIndex] = UnivariateRandom();
}
return new Sample (univariateRandomArray);
}
private static final Sample[] GenerateSampleArray (
final int drawCount,
final int sampleCount)
throws Exception
{
Sample[] sampleArray = new Sample[sampleCount];
for (int sampleIndex = 0; sampleIndex < sampleCount; ++sampleIndex)
{
sampleArray[sampleIndex] = GenerateSample (drawCount);
}
return sampleArray;
}
private static final TestStatisticEvaluator[] MakeTestStatisticEvaluatorArray()
throws Exception
{
return new TestStatisticEvaluator[]
{
new TestStatisticEvaluator()
{
public double evaluate (
final double[] drawArray)
throws Exception
{
double mean = 0.;
int drawCount = drawArray.length;
for (int drawIndex = 0; drawIndex < drawCount; ++drawIndex)
{
mean += drawArray[drawIndex];
}
return mean / drawCount;
}
}
};
}
private static final void SignificanceTest (
final ProbabilityIntegralTransformTest test,
final int drawCount,
final TestStatisticEvaluator testStatisticEvaluator,
final SignificanceTestSetting pTestSetting)
throws Exception
{
Sample testSample = GenerateSample (drawCount);
SignificanceTestOutcome significanceTest = test.significanceTest (
testSample.applyTestStatistic (testStatisticEvaluator),
pTestSetting
);
System.out.println (
"\t| " + FormatUtil.FormatDouble (significanceTest.testStatistic(), 1, 8, 1.) +
" | " + FormatUtil.FormatDouble (significanceTest.rightTailPValue(), 1, 8, 1.) +
" | " + FormatUtil.FormatDouble (significanceTest.leftTailPValue(), 1, 8, 1.) +
" | " + significanceTest.pass()
);
}
public static final void main (
final String[] argumentArray)
throws Exception
{
EnvManager.InitEnv ("");
int drawCount = 10000;
int sampleCount = 100;
int significanceTestCount = 20;
TestStatisticEvaluator[] testStatisticEvaluatorArray = MakeTestStatisticEvaluatorArray();
Ensemble ensemble = new Ensemble (
GenerateSampleArray (
drawCount,
sampleCount
),
testStatisticEvaluatorArray
);
ProbabilityIntegralTransformTest test = ensemble.significanceTest()[0];
SignificanceTestSetting significanceTestSettingRightTail = SignificanceTestSetting.FisherRightTail();
System.out.println ("\t|-------------------------------------------------||");
System.out.println ("\t| ENSEMBLE SIGNIFICANCE RIGHT TAIL TEST ||");
System.out.println ("\t|-------------------------------------------------||");
System.out.println ("\t| L -> R: ||");
System.out.println ("\t| - Test Statistic ||");
System.out.println ("\t| - Right Tail p-Value ||");
System.out.println ("\t| - Left Tail p-Value ||");
System.out.println ("\t| - Significance Test Status ||");
System.out.println ("\t|-------------------------------------------------||");
for (int significanceTest = 0; significanceTest < significanceTestCount; ++significanceTest)
{
SignificanceTest (
test,
drawCount,
testStatisticEvaluatorArray[0],
significanceTestSettingRightTail
);
}
System.out.println ("\t|-------------------------------------------------||");
SignificanceTestSetting significanceTestSettingLeftTail = SignificanceTestSetting.FisherLeftTail();
System.out.println ("\t|-------------------------------------------------||");
System.out.println ("\t| ENSEMBLE SIGNIFICANCE RIGHT TAIL TEST ||");
System.out.println ("\t|-------------------------------------------------||");
System.out.println ("\t| L -> R: ||");
System.out.println ("\t| - Test Statistic ||");
System.out.println ("\t| - Right Tail p-Value ||");
System.out.println ("\t| - Left Tail p-Value ||");
System.out.println ("\t| - Significance Test Status ||");
System.out.println ("\t|-------------------------------------------------||");
for (int significanceTest = 0; significanceTest < significanceTestCount; ++significanceTest)
{
SignificanceTest (
test,
drawCount,
testStatisticEvaluatorArray[0],
significanceTestSettingLeftTail
);
}
System.out.println ("\t|-------------------------------------------------||");
SignificanceTestSetting significanceTestSettingDoubleTail = SignificanceTestSetting.FisherDoubleTail();
System.out.println ("\t|-------------------------------------------------||");
System.out.println ("\t| ENSEMBLE SIGNIFICANCE DOUBLE TAIL TEST ||");
System.out.println ("\t|-------------------------------------------------||");
System.out.println ("\t| L -> R: ||");
System.out.println ("\t| - Test Statistic ||");
System.out.println ("\t| - Right Tail p-Value ||");
System.out.println ("\t| - Left Tail p-Value ||");
System.out.println ("\t| - Significance Test Status ||");
System.out.println ("\t|-------------------------------------------------||");
for (int significanceTest = 0; significanceTest < significanceTestCount; ++significanceTest)
{
SignificanceTest (
test,
drawCount,
testStatisticEvaluatorArray[0],
significanceTestSettingDoubleTail
);
}
System.out.println ("\t|-------------------------------------------------||");
EnvManager.TerminateEnv();
}
}