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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2024 Ralf Konrad Eckel
This file is part of QuantLib, a free-software/open-source library
for financial quantitative analysts and developers - http://quantlib.org/
QuantLib is free software: you can redistribute it and/or modify it
under the terms of the QuantLib license. You should have received a
copy of the license along with this program; if not, please email
<quantlib-dev@lists.sf.net>. The license is also available online at
<http://quantlib.org/license.shtml>.
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.
*/
#include "toplevelfixture.hpp"
#include <ql/math/randomnumbers/xoshiro256starstaruniformrng.hpp>
#include <ql/math/randomnumbers/zigguratgaussianrng.hpp>
#include <ql/math/statistics/incrementalstatistics.hpp>
#include <iostream>
#include <numeric>
using namespace QuantLib;
BOOST_FIXTURE_TEST_SUITE(QuantLibTests, TopLevelFixture)
BOOST_AUTO_TEST_SUITE(ZigguratGaussianTests)
BOOST_AUTO_TEST_CASE(testStatisticsOfNextReal) {
BOOST_TEST_MESSAGE("Testing ZigguratGaussianRng<Xoshiro256StarStarUniformRng>::nextReal() for "
"mean, variance, skewness and kurtosis...");
auto seed = 42UL;
auto uniformRandom = Xoshiro256StarStarUniformRng(seed);
auto random = ZigguratGaussianRng<Xoshiro256StarStarUniformRng>(uniformRandom);
auto randoms = IncrementalStatistics();
auto iterations = 10'000'000;
for (auto j = 0; j < iterations; ++j) {
Real next = random.next().value;
randoms.add(next);
}
auto mean = randoms.mean();
auto variance = randoms.variance();
auto skewness = randoms.skewness();
auto kurtosis = randoms.kurtosis();
if (std::abs(mean) > 0.001) {
BOOST_ERROR("Mean " << mean << " for seed " << seed << " is not close to 0.");
}
if (std::abs(1.0 - variance) > 0.005) {
BOOST_ERROR("Variance " << variance << " for seed " << seed << " is not close to 1.");
}
if (std::abs(skewness) > 0.001) {
BOOST_ERROR("Skewness " << skewness << " for seed " << seed << " is not close to 0.");
}
if (std::abs(kurtosis) > 0.03) {
BOOST_ERROR("Kurtosis " << kurtosis << " for seed " << seed << " is not close to 0.");
}
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
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