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// (C) Copyright Eric Niebler 2005.
// Use, modification and distribution are subject to the
// Boost Software License, Version 1.0. (See accompanying file
// LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
// Test case for weighted_p_square_quantile.hpp
#include <cmath> // for std::exp()
#include <boost/random.hpp>
#include <boost/test/unit_test.hpp>
#include <boost/test/tools/floating_point_comparison.hpp>
#include <boost/accumulators/numeric/functional/vector.hpp>
#include <boost/accumulators/numeric/functional/complex.hpp>
#include <boost/accumulators/numeric/functional/valarray.hpp>
#include <boost/accumulators/accumulators.hpp>
#include <boost/accumulators/statistics/stats.hpp>
#include <boost/accumulators/statistics/weighted_p_square_quantile.hpp>
using namespace boost;
using namespace unit_test;
using namespace boost::accumulators;
///////////////////////////////////////////////////////////////////////////////
// test_stat
//
void test_stat()
{
typedef accumulator_set<double, stats<tag::weighted_p_square_quantile>, double> accumulator_t;
// tolerance in %
double epsilon = 1;
// some random number generators
double mu4 = -1.0;
double mu5 = -1.0;
double mu6 = 1.0;
double mu7 = 1.0;
boost::lagged_fibonacci607 rng;
boost::normal_distribution<> mean_sigma4(mu4, 1);
boost::normal_distribution<> mean_sigma5(mu5, 1);
boost::normal_distribution<> mean_sigma6(mu6, 1);
boost::normal_distribution<> mean_sigma7(mu7, 1);
boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal4(rng, mean_sigma4);
boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal5(rng, mean_sigma5);
boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal6(rng, mean_sigma6);
boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal7(rng, mean_sigma7);
accumulator_t acc0(quantile_probability = 0.001);
accumulator_t acc1(quantile_probability = 0.025);
accumulator_t acc2(quantile_probability = 0.975);
accumulator_t acc3(quantile_probability = 0.999);
accumulator_t acc4(quantile_probability = 0.001);
accumulator_t acc5(quantile_probability = 0.025);
accumulator_t acc6(quantile_probability = 0.975);
accumulator_t acc7(quantile_probability = 0.999);
for (std::size_t i=0; i<100000; ++i)
{
double sample = rng();
acc0(sample, weight = 1.);
acc1(sample, weight = 1.);
acc2(sample, weight = 1.);
acc3(sample, weight = 1.);
double sample4 = normal4();
double sample5 = normal5();
double sample6 = normal6();
double sample7 = normal7();
acc4(sample4, weight = std::exp(-mu4 * (sample4 - 0.5 * mu4)));
acc5(sample5, weight = std::exp(-mu5 * (sample5 - 0.5 * mu5)));
acc6(sample6, weight = std::exp(-mu6 * (sample6 - 0.5 * mu6)));
acc7(sample7, weight = std::exp(-mu7 * (sample7 - 0.5 * mu7)));
}
// check for uniform distribution with weight = 1
BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc0), 0.001, 28 );
BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc1), 0.025, 5 );
BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc2), 0.975, epsilon );
BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc3), 0.999, epsilon );
// check for shifted standard normal distribution ("importance sampling")
BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc4), -3.090232, epsilon );
BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc5), -1.959963, epsilon );
BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc6), 1.959963, epsilon );
BOOST_CHECK_CLOSE( weighted_p_square_quantile(acc7), 3.090232, epsilon );
}
///////////////////////////////////////////////////////////////////////////////
// init_unit_test_suite
//
test_suite* init_unit_test_suite( int argc, char* argv[] )
{
test_suite *test = BOOST_TEST_SUITE("weighted_p_square_quantile test");
test->add(BOOST_TEST_CASE(&test_stat));
return test;
}
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