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Commons Math example source code file (UncorrelatedRandomVectorGeneratorTest.java)
The Commons Math UncorrelatedRandomVectorGeneratorTest.java source code//Licensed to the Apache Software Foundation (ASF) under one //or more contributor license agreements. See the NOTICE file //distributed with this work for additional information //regarding copyright ownership. The ASF licenses this file //to you 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. package org.apache.commons.math.random; import org.apache.commons.math.DimensionMismatchException; import org.apache.commons.math.linear.RealMatrix; import org.apache.commons.math.stat.descriptive.moment.VectorialCovariance; import org.apache.commons.math.stat.descriptive.moment.VectorialMean; import junit.framework.*; public class UncorrelatedRandomVectorGeneratorTest extends TestCase { public UncorrelatedRandomVectorGeneratorTest(String name) { super(name); mean = null; standardDeviation = null; generator = null; } public void testMeanAndCorrelation() throws DimensionMismatchException { VectorialMean meanStat = new VectorialMean(mean.length); VectorialCovariance covStat = new VectorialCovariance(mean.length, true); for (int i = 0; i < 10000; ++i) { double[] v = generator.nextVector(); meanStat.increment(v); covStat.increment(v); } double[] estimatedMean = meanStat.getResult(); double scale; RealMatrix estimatedCorrelation = covStat.getResult(); for (int i = 0; i < estimatedMean.length; ++i) { assertEquals(mean[i], estimatedMean[i], 0.07); for (int j = 0; j < i; ++j) { scale = standardDeviation[i] * standardDeviation[j]; assertEquals(0, estimatedCorrelation.getEntry(i, j) / scale, 0.03); } scale = standardDeviation[i] * standardDeviation[i]; assertEquals(1, estimatedCorrelation.getEntry(i, i) / scale, 0.025); } } @Override public void setUp() { mean = new double[] {0.0, 1.0, -3.0, 2.3}; standardDeviation = new double[] {1.0, 2.0, 10.0, 0.1}; RandomGenerator rg = new JDKRandomGenerator(); rg.setSeed(17399225432l); generator = new UncorrelatedRandomVectorGenerator(mean, standardDeviation, new GaussianRandomGenerator(rg)); } @Override public void tearDown() { mean = null; standardDeviation = null; generator = null; } private double[] mean; private double[] standardDeviation; private UncorrelatedRandomVectorGenerator generator; } Other Commons Math examples (source code examples)Here is a short list of links related to this Commons Math UncorrelatedRandomVectorGeneratorTest.java source code file: |
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