/*
Copyright (C) 2008 Richard Gomes
This source code is release under the BSD License.
This file is part of JQuantLib, a free-software/open-source library
for financial quantitative analysts and developers - http://jquantlib.org/
JQuantLib is free software: you can redistribute it and/or modify it
under the terms of the JQuantLib license. You should have received a
copy of the license along with this program; if not, please email
. The license is also available online at
.
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the license for more details.
JQuantLib is based on QuantLib. http://quantlib.org/
When applicable, the original copyright notice follows this notice.
*/
package org.jquantlib.testsuite.math.distributions;
import static org.junit.Assert.fail;
import org.jquantlib.QL;
import org.jquantlib.math.Closeness;
import org.jquantlib.math.distributions.InverseCumulativePoisson;
import org.junit.Test;
/**
* @author Dominik Holenstein
*/
public class InverseCumulativePoissonTest {
public InverseCumulativePoissonTest() {
QL.info("::::: " + this.getClass().getSimpleName() + " :::::");
}
@Test
public void testInverseCumulativePoissonDistribution() {
QL.info("running InverseCumulativePoissonDistribution test ....");
final InverseCumulativePoisson icp = new InverseCumulativePoisson(1.0);
final double data[] = { 0.2, 0.5, 0.9, 0.98, 0.99, 0.999, 0.9999, 0.99995,
0.99999, 0.999999, 0.9999999, 0.99999999 };
for (int i = 0; i < data.length; i++) {
if (!Closeness.isClose(icp.op(data[i]), i)) {
fail("failed to reproduce known value for x = " + data[i]
+ "\n" + "calculated: " + data[i] + "\n" + "expected: "
+ i);
}
}
QL.info("... test finished.");
}
}
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