weighted_p_square_quantile.cpp
来自「Boost provides free peer-reviewed portab」· C++ 代码 · 共 101 行
CPP
101 行
// (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/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, 15 ); 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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