/**
* Copyright (C) 2009 - present by OpenGamma Inc. and the OpenGamma group of companies
*
* Please see distribution for license.
*/
package com.opengamma.analytics.math.statistics.estimation;
import static org.testng.AssertJUnit.assertEquals;
import org.testng.annotations.Test;
import cern.jet.random.engine.MersenneTwister;
import cern.jet.random.engine.MersenneTwister64;
import com.opengamma.analytics.math.statistics.distribution.NormalDistribution;
import com.opengamma.analytics.math.statistics.distribution.ProbabilityDistribution;
/**
*
*/
public class NormalDistributionMaximumLikelihoodEstimatorTest {
private static final DistributionParameterEstimator<Double> ESTIMATOR = new NormalDistributionMaximumLikelihoodEstimator();
@Test(expectedExceptions = IllegalArgumentException.class)
public void testNull() {
ESTIMATOR.evaluate((double[]) null);
}
@Test(expectedExceptions = IllegalArgumentException.class)
public void testEmpty() {
ESTIMATOR.evaluate(new double[0]);
}
@Test
public void test() {
final int n = 500000;
final double eps = 1e-2;
final double mu = -1.3;
final double sigma = 0.4;
final ProbabilityDistribution<Double> p1 = new NormalDistribution(mu, sigma, new MersenneTwister64(MersenneTwister.DEFAULT_SEED));
final double[] x = new double[n];
for (int i = 0; i < n; i++) {
x[i] = p1.nextRandom();
}
final NormalDistribution p2 = (NormalDistribution) ESTIMATOR.evaluate(x);
assertEquals(p2.getMean(), mu, eps);
assertEquals(p2.getStandardDeviation(), sigma, eps);
}
}