732 lines
34 KiB
C++
732 lines
34 KiB
C++
// (C) Copyright John Maddock 2007.
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// Use, modification and distribution are subject to the
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// Boost Software License, Version 1.0. (See accompanying file
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// LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
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#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
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#include <boost/math/concepts/real_concept.hpp>
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#define BOOST_TEST_MAIN
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#include <boost/test/unit_test.hpp>
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#include <boost/test/tools/floating_point_comparison.hpp>
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#include <boost/math/distributions/non_central_t.hpp>
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#include <boost/type_traits/is_floating_point.hpp>
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#include <boost/array.hpp>
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#include "functor.hpp"
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#include "test_out_of_range.hpp"
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#include "handle_test_result.hpp"
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#include "table_type.hpp"
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#define BOOST_CHECK_CLOSE_EX(a, b, prec, i) \
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{\
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unsigned int failures = boost::unit_test::results_collector.results( boost::unit_test::framework::current_test_case().p_id ).p_assertions_failed;\
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BOOST_CHECK_CLOSE(a, b, prec); \
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if(failures != boost::unit_test::results_collector.results( boost::unit_test::framework::current_test_case().p_id ).p_assertions_failed)\
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{\
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std::cerr << "Failure was at row " << i << std::endl;\
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std::cerr << std::setprecision(35); \
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std::cerr << "{ " << data[i][0] << " , " << data[i][1] << " , " << data[i][2];\
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std::cerr << " , " << data[i][3] << " , " << data[i][4] << " } " << std::endl;\
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}\
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}
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#define BOOST_CHECK_EX(a, i) \
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{\
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unsigned int failures = boost::unit_test::results_collector.results( boost::unit_test::framework::current_test_case().p_id ).p_assertions_failed;\
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BOOST_CHECK(a); \
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if(failures != boost::unit_test::results_collector.results( boost::unit_test::framework::current_test_case().p_id ).p_assertions_failed)\
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{\
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std::cerr << "Failure was at row " << i << std::endl;\
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std::cerr << std::setprecision(35); \
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std::cerr << "{ " << data[i][0] << " , " << data[i][1] << " , " << data[i][2];\
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std::cerr << " , " << data[i][3] << " , " << data[i][4] << " } " << std::endl;\
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}\
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}
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template <class RealType>
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RealType naive_pdf(RealType v, RealType delta, RealType x)
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{
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}
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template <class RealType>
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RealType naive_mean(RealType v, RealType delta)
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{
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using boost::math::tgamma;
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return delta * sqrt(v / 2) * tgamma((v - 1) / 2) / tgamma(v / 2);
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}
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float naive_mean(float v, float delta)
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{
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return (float)naive_mean((double)v, (double)delta);
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}
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template <class RealType>
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RealType naive_variance(RealType v, RealType delta)
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{
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using boost::math::tgamma;
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RealType r = tgamma((v - 1) / 2) / tgamma(v / 2);
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r *= r;
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r *= -delta * delta * v / 2;
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r += (1 + delta * delta) * v / (v - 2);
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return r;
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}
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float naive_variance(float v, float delta)
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{
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return (float)naive_variance((double)v, (double)delta);
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}
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template <class RealType>
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RealType naive_skewness(RealType v, RealType delta)
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{
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using boost::math::tgamma;
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RealType tgr = tgamma((v - 1) / 2) / tgamma(v / 2);
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RealType r = delta * sqrt(v) * tgamma((v - 1) / 2)
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* (v * (-3 + delta * delta + 2 * v) / ((-3 + v) * (-2 + v))
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- 2 * ((1 + delta * delta) * v / (-2 + v) - delta * delta * v * tgr * tgr / 2));
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r /= boost::math::constants::root_two<RealType>()
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* pow(((1 + delta*delta) * v / (-2 + v) - delta*delta*v*tgr*tgr / 2), RealType(1.5f))
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* tgamma(v / 2);
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return r;
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}
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float naive_skewness(float v, float delta)
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{
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return (float)naive_skewness((double)v, (double)delta);
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}
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template <class RealType>
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RealType naive_kurtosis_excess(RealType v, RealType delta)
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{
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using boost::math::tgamma;
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RealType tgr = tgamma((v - 1) / 2) / tgamma(v / 2);
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RealType r = -delta * delta * v * tgr * tgr / 2;
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r *= v * (delta * delta * (1 + v) + 3 * (-5 + 3 * v)) / ((-3 + v)*(-2 + v))
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- 3 * ((1 + delta * delta) * v / (-2 + v) - delta * delta * v * tgr * tgr / 2);
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r += (3 + 6 * delta * delta + delta * delta * delta * delta)* v * v
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/ ((-4 + v) * (-2 + v));
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r /= (1 + delta*delta)*v / (-2 + v) - delta*delta*v *tgr*tgr / 2;
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r /= (1 + delta*delta)*v / (-2 + v) - delta*delta*v *tgr*tgr / 2;
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return r;
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}
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float naive_kurtosis_excess(float v, float delta)
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{
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return (float)naive_kurtosis_excess((double)v, (double)delta);
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}
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template <class RealType>
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void test_spot(
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RealType df, // Degrees of freedom
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RealType ncp, // non-centrality param
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RealType t, // T statistic
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RealType P, // CDF
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RealType Q, // Complement of CDF
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RealType tol) // Test tolerance
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{
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// An extra fudge factor for real_concept which has a less accurate tgamma:
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RealType tolerance_tgamma_extra = std::numeric_limits<RealType>::is_specialized ? 1 : 5;
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boost::math::non_central_t_distribution<RealType> dist(df, ncp);
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BOOST_CHECK_CLOSE(
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cdf(dist, t), P, tol);
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#ifndef BOOST_NO_EXCEPTIONS
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try{
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BOOST_CHECK_CLOSE(
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mean(dist), naive_mean(df, ncp), tol);
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BOOST_CHECK_CLOSE(
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variance(dist), naive_variance(df, ncp), tol);
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BOOST_CHECK_CLOSE(
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skewness(dist), naive_skewness(df, ncp), tol * 10 * tolerance_tgamma_extra);
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BOOST_CHECK_CLOSE(
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kurtosis_excess(dist), naive_kurtosis_excess(df, ncp), tol * 50 * tolerance_tgamma_extra);
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BOOST_CHECK_CLOSE(
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kurtosis(dist), 3 + naive_kurtosis_excess(df, ncp), tol * 50 * tolerance_tgamma_extra);
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}
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catch(const std::domain_error&)
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{
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}
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#endif
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/*
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BOOST_CHECK_CLOSE(
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pdf(dist, t), naive_pdf(dist.degrees_of_freedom(), ncp, t), tol * 50);
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*/
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if((P < 0.99) && (Q < 0.99))
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{
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//
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// We can only check this if P is not too close to 1,
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// so that we can guarantee Q is reasonably free of error:
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//
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BOOST_CHECK_CLOSE(
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cdf(complement(dist, t)), Q, tol);
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BOOST_CHECK_CLOSE(
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quantile(dist, P), t, tol * 10);
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BOOST_CHECK_CLOSE(
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quantile(complement(dist, Q)), t, tol * 10);
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/* Removed because can give more than one solution.
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BOOST_CHECK_CLOSE(
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dist.find_degrees_of_freedom(ncp, t, P), df, tol * 10);
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BOOST_CHECK_CLOSE(
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dist.find_degrees_of_freedom(boost::math::complement(ncp, t, Q)), df, tol * 10);
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BOOST_CHECK_CLOSE(
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dist.find_non_centrality(df, t, P), ncp, tol * 10);
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BOOST_CHECK_CLOSE(
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dist.find_non_centrality(boost::math::complement(df, t, Q)), ncp, tol * 10);
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*/
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}
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}
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template <class RealType> // Any floating-point type RealType.
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void test_spots(RealType)
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{
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using namespace std;
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//
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// Approx limit of test data is 12 digits expressed here as a percentage:
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//
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RealType tolerance = (std::max)(
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boost::math::tools::epsilon<RealType>(),
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(RealType)5e-12f) * 100;
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//
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// At float precision we need to up the tolerance, since
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// the input values are rounded off to inexact quantities
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// the results get thrown off by a noticeable amount.
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//
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if(boost::math::tools::digits<RealType>() < 50)
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tolerance *= 50;
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if(boost::is_floating_point<RealType>::value != 1)
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tolerance *= 20; // real_concept special functions are less accurate
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cout << "Tolerance = " << tolerance << "%." << endl;
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//
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// Test data is taken from:
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//
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// Computing discrete mixtures of continuous
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// distributions: noncentral chisquare, noncentral t
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// and the distribution of the square of the sample
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// multiple correlation coeficient.
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// Denise Benton, K. Krishnamoorthy.
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// Computational Statistics & Data Analysis 43 (2003) 249 - 267
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//
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test_spot(
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static_cast<RealType>(3), // degrees of freedom
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static_cast<RealType>(1), // non centrality
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static_cast<RealType>(2.34), // T
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static_cast<RealType>(0.801888999613917), // Probability of result (CDF), P
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static_cast<RealType>(1 - 0.801888999613917), // Q = 1 - P
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tolerance);
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test_spot(
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static_cast<RealType>(126), // degrees of freedom
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static_cast<RealType>(-2), // non centrality
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static_cast<RealType>(-4.33), // T
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static_cast<RealType>(1.252846196792878e-2), // Probability of result (CDF), P
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static_cast<RealType>(1 - 1.252846196792878e-2), // Q = 1 - P
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tolerance);
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test_spot(
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static_cast<RealType>(20), // degrees of freedom
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static_cast<RealType>(23), // non centrality
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static_cast<RealType>(23), // T
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static_cast<RealType>(0.460134400391924), // Probability of result (CDF), P
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static_cast<RealType>(1 - 0.460134400391924), // Q = 1 - P
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tolerance);
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test_spot(
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static_cast<RealType>(20), // degrees of freedom
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static_cast<RealType>(33), // non centrality
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static_cast<RealType>(34), // T
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static_cast<RealType>(0.532008386378725), // Probability of result (CDF), P
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static_cast<RealType>(1 - 0.532008386378725), // Q = 1 - P
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tolerance);
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test_spot(
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static_cast<RealType>(12), // degrees of freedom
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static_cast<RealType>(38), // non centrality
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static_cast<RealType>(39), // T
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static_cast<RealType>(0.495868184917805), // Probability of result (CDF), P
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static_cast<RealType>(1 - 0.495868184917805), // Q = 1 - P
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tolerance);
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test_spot(
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static_cast<RealType>(12), // degrees of freedom
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static_cast<RealType>(39), // non centrality
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static_cast<RealType>(39), // T
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static_cast<RealType>(0.446304024668836), // Probability of result (CDF), P
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static_cast<RealType>(1 - 0.446304024668836), // Q = 1 - P
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tolerance);
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test_spot(
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static_cast<RealType>(200), // degrees of freedom
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static_cast<RealType>(38), // non centrality
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static_cast<RealType>(39), // T
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static_cast<RealType>(0.666194209961795), // Probability of result (CDF), P
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static_cast<RealType>(1 - 0.666194209961795), // Q = 1 - P
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tolerance);
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test_spot(
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static_cast<RealType>(200), // degrees of freedom
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static_cast<RealType>(42), // non centrality
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static_cast<RealType>(40), // T
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static_cast<RealType>(0.179292265426085), // Probability of result (CDF), P
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static_cast<RealType>(1 - 0.179292265426085), // Q = 1 - P
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tolerance);
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// From https://svn.boost.org/trac/boost/ticket/10480.
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// Test value from Mathematica N[CDF[NoncentralStudentTDistribution[2, 4], 5], 35]:
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test_spot(
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static_cast<RealType>(2), // degrees of freedom
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static_cast<RealType>(4), // non centrality
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static_cast<RealType>(5), // T
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static_cast<RealType>(0.53202069866995310466912357978934321L), // Probability of result (CDF), P
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static_cast<RealType>(1 - 0.53202069866995310466912357978934321L), // Q = 1 - P
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tolerance);
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/* This test fails
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"Result of tgamma is too large to represent" at naive_mean check for max and infinity.
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if (std::numeric_limits<RealType>::has_infinity)
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{
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test_spot(
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//static_cast<RealType>(std::numeric_limits<RealType>::infinity()), // degrees of freedom
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static_cast<RealType>((std::numeric_limits<RealType>::max)()), // degrees of freedom
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static_cast<RealType>(10), // non centrality
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static_cast<RealType>(11), // T
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static_cast<RealType>(0.84134474606854293), // Probability of result (CDF), P
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static_cast<RealType>(0.15865525393145707), // Q = 1 - P
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tolerance);
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}
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*/
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boost::math::non_central_t_distribution<RealType> dist(static_cast<RealType>(8), static_cast<RealType>(12));
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BOOST_CHECK_CLOSE(pdf(dist, 12), static_cast<RealType>(1.235329715425894935157684607751972713457e-1L), tolerance);
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BOOST_CHECK_CLOSE(pdf(boost::math::non_central_t_distribution<RealType>(126, -2), -4), static_cast<RealType>(5.797932289365814702402873546466798025787e-2L), tolerance);
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BOOST_CHECK_CLOSE(pdf(boost::math::non_central_t_distribution<RealType>(126, 2), 4), static_cast<RealType>(5.797932289365814702402873546466798025787e-2L), tolerance);
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BOOST_CHECK_CLOSE(pdf(boost::math::non_central_t_distribution<RealType>(126, 2), 0), static_cast<RealType>(5.388394890639957139696546086044839573749e-2L), tolerance);
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// Error handling checks:
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//check_out_of_range<boost::math::non_central_t_distribution<RealType> >(1, 1); // Fails one check because df for this distribution *can* be infinity.
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BOOST_MATH_CHECK_THROW(pdf(boost::math::non_central_t_distribution<RealType>(0, 1), 0), std::domain_error);
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BOOST_MATH_CHECK_THROW(pdf(boost::math::non_central_t_distribution<RealType>(-1, 1), 0), std::domain_error);
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BOOST_MATH_CHECK_THROW(quantile(boost::math::non_central_t_distribution<RealType>(1, 1), -1), std::domain_error);
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BOOST_MATH_CHECK_THROW(quantile(boost::math::non_central_t_distribution<RealType>(1, 1), 2), std::domain_error);
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} // template <class RealType>void test_spots(RealType)
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template <class T>
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T nct_cdf(T df, T nc, T x)
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{
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return cdf(boost::math::non_central_t_distribution<T>(df, nc), x);
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}
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template <class T>
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T nct_ccdf(T df, T nc, T x)
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{
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return cdf(complement(boost::math::non_central_t_distribution<T>(df, nc), x));
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}
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template <typename Real, typename T>
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void do_test_nc_t(T& data, const char* type_name, const char* test)
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{
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typedef Real value_type;
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std::cout << "Testing: " << test << std::endl;
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#ifdef NC_T_CDF_FUNCTION_TO_TEST
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value_type(*fp1)(value_type, value_type, value_type) = NC_T_CDF_FUNCTION_TO_TEST;
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#else
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value_type(*fp1)(value_type, value_type, value_type) = nct_cdf;
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#endif
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boost::math::tools::test_result<value_type> result;
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#if !(defined(ERROR_REPORTING_MODE) && !defined(NC_T_CDF_FUNCTION_TO_TEST))
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result = boost::math::tools::test_hetero<Real>(
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data,
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bind_func<Real>(fp1, 0, 1, 2),
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extract_result<Real>(3));
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handle_test_result(result, data[result.worst()], result.worst(),
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type_name, "non central t CDF", test);
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#endif
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#if !(defined(ERROR_REPORTING_MODE) && !defined(NC_T_CCDF_FUNCTION_TO_TEST))
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#ifdef NC_T_CCDF_FUNCTION_TO_TEST
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fp1 = NC_T_CCDF_FUNCTION_TO_TEST;
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#else
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fp1 = nct_ccdf;
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#endif
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result = boost::math::tools::test_hetero<Real>(
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data,
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bind_func<Real>(fp1, 0, 1, 2),
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extract_result<Real>(4));
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handle_test_result(result, data[result.worst()], result.worst(),
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type_name, "non central t CDF complement", test);
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std::cout << std::endl;
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#endif
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}
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template <typename Real, typename T>
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void quantile_sanity_check(T& data, const char* type_name, const char* test)
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{
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#ifndef ERROR_REPORTING_MODE
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typedef Real value_type;
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//
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// Tests with type real_concept take rather too long to run, so
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// for now we'll disable them:
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//
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if(!boost::is_floating_point<value_type>::value)
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return;
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std::cout << "Testing: " << type_name << " quantile sanity check, with tests " << test << std::endl;
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//
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// These sanity checks test for a round trip accuracy of one half
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// of the bits in T, unless T is type float, in which case we check
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// for just one decimal digit. The problem here is the sensitivity
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// of the functions, not their accuracy. This test data was generated
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// for the forward functions, which means that when it is used as
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// the input to the inverses then it is necessarily inexact. This rounding
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// of the input is what makes the data unsuitable for use as an accuracy check,
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// and also demonstrates that you can't in general round-trip these functions.
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// It is however a useful sanity check.
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//
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value_type precision = static_cast<value_type>(ldexp(1.0, 1 - boost::math::policies::digits<value_type, boost::math::policies::policy<> >() / 2)) * 100;
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if(boost::math::policies::digits<value_type, boost::math::policies::policy<> >() < 50)
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precision = 1; // 1% or two decimal digits, all we can hope for when the input is truncated to float
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for(unsigned i = 0; i < data.size(); ++i)
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{
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if(data[i][3] == 0)
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{
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BOOST_CHECK(0 == quantile(boost::math::non_central_t_distribution<value_type>(data[i][0], data[i][1]), data[i][3]));
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}
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else if(data[i][3] < 0.9999f)
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{
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value_type p = quantile(boost::math::non_central_t_distribution<value_type>(data[i][0], data[i][1]), data[i][3]);
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value_type pt = data[i][2];
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BOOST_CHECK_CLOSE_EX(pt, p, precision, i);
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}
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if(data[i][4] == 0)
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{
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BOOST_CHECK(0 == quantile(complement(boost::math::non_central_t_distribution<value_type>(data[i][0], data[i][1]), data[i][3])));
|
|
}
|
|
else if(data[i][4] < 0.9999f)
|
|
{
|
|
value_type p = quantile(complement(boost::math::non_central_t_distribution<value_type>(data[i][0], data[i][1]), data[i][4]));
|
|
value_type pt = data[i][2];
|
|
BOOST_CHECK_CLOSE_EX(pt, p, precision, i);
|
|
}
|
|
if(boost::math::tools::digits<value_type>() > 50)
|
|
{
|
|
//
|
|
// Sanity check mode, the accuracy of
|
|
// the mode is at *best* the square root of the accuracy of the PDF:
|
|
//
|
|
#ifndef BOOST_NO_EXCEPTIONS
|
|
try{
|
|
value_type m = mode(boost::math::non_central_t_distribution<value_type>(data[i][0], data[i][1]));
|
|
value_type p = pdf(boost::math::non_central_t_distribution<value_type>(data[i][0], data[i][1]), m);
|
|
value_type delta = (std::max)(fabs(m * sqrt(precision) * 50), sqrt(precision) * 50);
|
|
BOOST_CHECK_EX(pdf(boost::math::non_central_t_distribution<value_type>(data[i][0], data[i][1]), m + delta) <= p, i);
|
|
BOOST_CHECK_EX(pdf(boost::math::non_central_t_distribution<value_type>(data[i][0], data[i][1]), m - delta) <= p, i);
|
|
}
|
|
catch(const boost::math::evaluation_error&) {}
|
|
#endif
|
|
#if 0
|
|
//
|
|
// Sanity check degrees-of-freedom finder, don't bother at float
|
|
// precision though as there's not enough data in the probability
|
|
// values to get back to the correct degrees of freedom or
|
|
// non-centrality parameter:
|
|
//
|
|
try{
|
|
if((data[i][3] < 0.99) && (data[i][3] != 0))
|
|
{
|
|
BOOST_CHECK_CLOSE_EX(
|
|
boost::math::non_central_t_distribution<value_type>::find_degrees_of_freedom(data[i][1], data[i][2], data[i][3]),
|
|
data[i][0], precision, i);
|
|
BOOST_CHECK_CLOSE_EX(
|
|
boost::math::non_central_t_distribution<value_type>::find_non_centrality(data[i][0], data[i][2], data[i][3]),
|
|
data[i][1], precision, i);
|
|
}
|
|
if((data[i][4] < 0.99) && (data[i][4] != 0))
|
|
{
|
|
BOOST_CHECK_CLOSE_EX(
|
|
boost::math::non_central_t_distribution<value_type>::find_degrees_of_freedom(boost::math::complement(data[i][1], data[i][2], data[i][4])),
|
|
data[i][0], precision, i);
|
|
BOOST_CHECK_CLOSE_EX(
|
|
boost::math::non_central_t_distribution<value_type>::find_non_centrality(boost::math::complement(data[i][0], data[i][2], data[i][4])),
|
|
data[i][1], precision, i);
|
|
}
|
|
}
|
|
catch(const std::exception& e)
|
|
{
|
|
BOOST_ERROR(e.what());
|
|
}
|
|
#endif
|
|
}
|
|
}
|
|
#endif
|
|
}
|
|
|
|
template <typename T>
|
|
void test_accuracy(T, const char* type_name)
|
|
{
|
|
#include "nct.ipp"
|
|
do_test_nc_t<T>(nct, type_name, "Non Central T");
|
|
quantile_sanity_check<T>(nct, type_name, "Non Central T");
|
|
if(std::numeric_limits<T>::is_specialized)
|
|
{
|
|
//
|
|
// Don't run these tests for real_concept: they take too long and don't converge
|
|
// without numeric_limits and lanczos support:
|
|
//
|
|
#include "nct_small_delta.ipp"
|
|
do_test_nc_t<T>(nct_small_delta, type_name, "Non Central T (small non-centrality)");
|
|
quantile_sanity_check<T>(nct_small_delta, type_name, "Non Central T (small non-centrality)");
|
|
#include "nct_asym.ipp"
|
|
do_test_nc_t<T>(nct_asym, type_name, "Non Central T (large parameters)");
|
|
quantile_sanity_check<T>(nct_asym, type_name, "Non Central T (large parameters)");
|
|
}
|
|
}
|
|
|
|
|
|
template <class RealType>
|
|
void test_big_df(RealType)
|
|
{
|
|
using namespace boost::math;
|
|
|
|
if(typeid(RealType) != typeid(boost::math::concepts::real_concept))
|
|
{ // Ordinary floats only.
|
|
// Could also test if (std::numeric_limits<RealType>::is_specialized);
|
|
|
|
RealType tolerance = 10 * boost::math::tools::epsilon<RealType>(); // static_cast<RealType>(1e-14); //
|
|
std::cout.precision(17); // Note: need to reset after calling BOOST_CHECK_s
|
|
// due to buglet in Boost.test that fails to restore precision corrrectly.
|
|
|
|
// Test for large degrees of freedom when should be same as normal.
|
|
RealType inf =
|
|
(std::numeric_limits<RealType>::has_infinity) ?
|
|
std::numeric_limits<RealType>::infinity()
|
|
:
|
|
boost::math::tools::max_value<RealType>();
|
|
RealType nan = std::numeric_limits<RealType>::quiet_NaN();
|
|
|
|
// Tests for df = max_value and infinity.
|
|
RealType max_val = boost::math::tools::max_value<RealType>();
|
|
non_central_t_distribution<RealType> maxdf(max_val, 0);
|
|
BOOST_CHECK_EQUAL(maxdf.degrees_of_freedom(), max_val);
|
|
|
|
non_central_t_distribution<RealType> infdf(inf, 0);
|
|
BOOST_CHECK_EQUAL(infdf.degrees_of_freedom(), inf);
|
|
BOOST_CHECK_EQUAL(mean(infdf), 0);
|
|
BOOST_CHECK_EQUAL(mean(maxdf), 0);
|
|
BOOST_CHECK_EQUAL(variance(infdf), 1);
|
|
BOOST_CHECK_EQUAL(variance(maxdf), 1);
|
|
BOOST_CHECK_EQUAL(skewness(infdf), 0);
|
|
BOOST_CHECK_EQUAL(skewness(maxdf), 0);
|
|
BOOST_CHECK_EQUAL(kurtosis_excess(infdf), 3);
|
|
BOOST_CHECK_CLOSE_FRACTION(kurtosis_excess(maxdf), static_cast<RealType>(3), tolerance);
|
|
|
|
// Bad df examples.
|
|
#ifndef BOOST_NO_EXCEPTIONS
|
|
BOOST_MATH_CHECK_THROW(non_central_t_distribution<RealType> minfdf(-inf, 0), std::domain_error);
|
|
BOOST_MATH_CHECK_THROW(non_central_t_distribution<RealType> minfdf(nan, 0), std::domain_error);
|
|
BOOST_MATH_CHECK_THROW(non_central_t_distribution<RealType> minfdf(-nan, 0), std::domain_error);
|
|
#else
|
|
BOOST_MATH_CHECK_THROW(non_central_t_distribution<RealType>(-inf, 0), std::domain_error);
|
|
BOOST_MATH_CHECK_THROW(non_central_t_distribution<RealType>(nan, 0), std::domain_error);
|
|
BOOST_MATH_CHECK_THROW(non_central_t_distribution<RealType>(-nan, 0), std::domain_error);
|
|
#endif
|
|
|
|
|
|
// BOOST_CHECK_CLOSE_FRACTION(pdf(infdf, 0), static_cast<RealType>(0.3989422804014326779399460599343818684759L), tolerance);
|
|
BOOST_CHECK_CLOSE_FRACTION(pdf(maxdf, 0), boost::math::constants::one_div_root_two_pi<RealType>(), tolerance);
|
|
BOOST_CHECK_CLOSE_FRACTION(pdf(infdf, 0), boost::math::constants::one_div_root_two_pi<RealType>(), tolerance);
|
|
BOOST_CHECK_CLOSE_FRACTION(cdf(infdf, 0), boost::math::constants::half<RealType>(), tolerance);
|
|
BOOST_CHECK_CLOSE_FRACTION(cdf(maxdf, 0), boost::math::constants::half<RealType>(), tolerance);
|
|
|
|
// non-centrality delta = 10
|
|
// Degrees of freedom = Max value and = infinity should be very close.
|
|
non_central_t_distribution<RealType> maxdf10(max_val, 10);
|
|
non_central_t_distribution<RealType> infdf10(inf, 10);
|
|
BOOST_CHECK_EQUAL(infdf10.degrees_of_freedom(), inf);
|
|
BOOST_CHECK_EQUAL(infdf10.non_centrality(), 10);
|
|
BOOST_CHECK_EQUAL(mean(infdf10), 10);
|
|
BOOST_CHECK_CLOSE_FRACTION(mean(maxdf10), static_cast<RealType>(10), tolerance);
|
|
|
|
BOOST_CHECK_CLOSE_FRACTION(pdf(infdf10, 11), pdf(maxdf10, 11), tolerance); //
|
|
|
|
BOOST_CHECK_CLOSE_FRACTION(cdf(complement(infdf10, 11)), 1 - cdf(infdf10, 11), tolerance); //
|
|
BOOST_CHECK_CLOSE_FRACTION(cdf(complement(maxdf10, 11)), 1 - cdf(maxdf10, 11), tolerance); //
|
|
BOOST_CHECK_CLOSE_FRACTION(cdf(complement(infdf10, 11)), 1 - cdf(maxdf10, 11), tolerance); //
|
|
std::cout.precision(17);
|
|
//std::cout << "cdf(maxdf10, 11) = " << cdf(maxdf10, 11) << ' ' << cdf(complement(maxdf10, 11)) << endl;
|
|
//std::cout << "cdf(infdf10, 11) = " << cdf(infdf10, 11) << ' ' << cdf(complement(infdf10, 11)) << endl;
|
|
//std::cout << "quantile(maxdf10, 0.5) = " << quantile(maxdf10, 0.5) << std::endl; // quantile(maxdf10, 0.5) = 10.000000000000004
|
|
//std::cout << "quantile(infdf10, 0.5) = " << ' ' << quantile(infdf10, 0.5) << std::endl; // quantile(infdf10, 0.5) = 10
|
|
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(infdf10, 0.5), static_cast<RealType>(10), tolerance);
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(maxdf10, 0.5), static_cast<RealType>(10), tolerance);
|
|
|
|
BOOST_TEST_MESSAGE("non_central_t_distribution<RealType> infdf100(inf, 100);");
|
|
non_central_t_distribution<RealType> infdf100(inf, 100);
|
|
BOOST_TEST_MESSAGE("non_central_t_distribution<RealType> maxdf100(max_val, 100);");
|
|
non_central_t_distribution<RealType> maxdf100(max_val, 100);
|
|
BOOST_TEST_MESSAGE("BOOST_CHECK_CLOSE_FRACTION(quantile(infdf100, 0.5), static_cast<RealType>(100), tolerance);");
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(infdf100, 0.5), static_cast<RealType>(100), tolerance);
|
|
BOOST_TEST_MESSAGE("BOOST_CHECK_CLOSE_FRACTION(quantile(maxdf100, 0.5), static_cast<RealType>(100), tolerance);");
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(maxdf100, 0.5), static_cast<RealType>(100), tolerance);
|
|
{ // Loop back.
|
|
RealType p = static_cast<RealType>(0.01);
|
|
RealType x = quantile(infdf10, p);
|
|
RealType c = cdf(infdf10, x);
|
|
BOOST_CHECK_CLOSE_FRACTION(c, p, tolerance);
|
|
}
|
|
{
|
|
RealType q = static_cast<RealType>(0.99);
|
|
RealType x = quantile(complement(infdf10, q));
|
|
RealType c = cdf(complement(infdf10, x));
|
|
BOOST_CHECK_CLOSE_FRACTION(c, q, tolerance);
|
|
}
|
|
{ // Loop back.
|
|
RealType p = static_cast<RealType>(0.99);
|
|
RealType x = quantile(infdf10, p);
|
|
RealType c = cdf(infdf10, x);
|
|
BOOST_CHECK_CLOSE_FRACTION(c, p, tolerance);
|
|
}
|
|
{
|
|
RealType q = static_cast<RealType>(0.01);
|
|
RealType x = quantile(complement(infdf10, q));
|
|
RealType c = cdf(complement(infdf10, x));
|
|
BOOST_CHECK_CLOSE_FRACTION(c, q, tolerance * 2); // c{0.0100000128} and q{0.00999999978}
|
|
}
|
|
|
|
//RealType cinf = quantile(infdf10, 0.25);
|
|
//std::cout << cinf << ' ' << cdf(infdf10, cinf) << std::endl; // 9.32551 0.25
|
|
|
|
//RealType cmax = quantile(maxdf10, 0.25);
|
|
//std::cout << cmax << ' ' << cdf(maxdf10, cmax) << std::endl; // 9.32551 0.25
|
|
|
|
//RealType cinfc = quantile(complement(infdf10, 0.75));
|
|
//std::cout << cinfc << ' ' << cdf(infdf10, cinfc) << std::endl; // 9.32551 0.25
|
|
|
|
//RealType cmaxc = quantile(complement(maxdf10, 0.75));
|
|
//std::cout << cmaxc << ' ' << cdf(maxdf10, cmaxc) << std::endl; // 9.32551 0.25
|
|
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(infdf10, 0.5), quantile(maxdf10, 0.5), tolerance); //
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(infdf10, 0.2), quantile(maxdf10, 0.2), tolerance); //
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(infdf10, 0.8), quantile(maxdf10, 0.8), tolerance); //
|
|
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(infdf10, 0.25), quantile(complement(infdf10, 0.75)), tolerance); //
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(complement(infdf10, 0.5)), quantile(complement(maxdf10, 0.5)), tolerance); //
|
|
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(maxdf10, 0.25), quantile(complement(maxdf10, 0.75)), tolerance); //
|
|
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(infdf10, 0.99), quantile(complement(infdf10, 0.01)), tolerance); //
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(infdf10, 0.4), quantile(complement(infdf10, 0.6)), tolerance); //
|
|
BOOST_CHECK_CLOSE_FRACTION(quantile(infdf10, 0.01), quantile(complement(infdf10, 1 - 0.01)), tolerance); //
|
|
}
|
|
} // void test_big_df(RealType)
|
|
|
|
template <class RealType>
|
|
void test_ignore_policy(RealType)
|
|
{
|
|
// Check on returns when errors are ignored.
|
|
if((typeid(RealType) != typeid(boost::math::concepts::real_concept))
|
|
&& std::numeric_limits<RealType>::has_infinity
|
|
&& std::numeric_limits<RealType>::has_quiet_NaN
|
|
)
|
|
{ // Ordinary floats only.
|
|
|
|
using namespace boost::math;
|
|
// RealType inf = std::numeric_limits<RealType>::infinity();
|
|
RealType nan = std::numeric_limits<RealType>::quiet_NaN();
|
|
|
|
using boost::math::policies::policy;
|
|
// Types of error whose action can be altered by policies:.
|
|
//using boost::math::policies::evaluation_error;
|
|
//using boost::math::policies::domain_error;
|
|
//using boost::math::policies::overflow_error;
|
|
//using boost::math::policies::underflow_error;
|
|
//using boost::math::policies::domain_error;
|
|
//using boost::math::policies::pole_error;
|
|
|
|
//// Actions on error (in enum error_policy_type):
|
|
//using boost::math::policies::errno_on_error;
|
|
//using boost::math::policies::ignore_error;
|
|
//using boost::math::policies::throw_on_error;
|
|
//using boost::math::policies::denorm_error;
|
|
//using boost::math::policies::pole_error;
|
|
//using boost::math::policies::user_error;
|
|
|
|
typedef policy<
|
|
boost::math::policies::domain_error<boost::math::policies::ignore_error>,
|
|
boost::math::policies::overflow_error<boost::math::policies::ignore_error>,
|
|
boost::math::policies::underflow_error<boost::math::policies::ignore_error>,
|
|
boost::math::policies::denorm_error<boost::math::policies::ignore_error>,
|
|
boost::math::policies::pole_error<boost::math::policies::ignore_error>,
|
|
boost::math::policies::evaluation_error<boost::math::policies::ignore_error>
|
|
> ignore_all_policy;
|
|
|
|
typedef non_central_t_distribution<RealType, ignore_all_policy> ignore_error_non_central_t;
|
|
|
|
// Only test NaN and infinity if type has these features (realconcept returns zero).
|
|
// Integers are always converted to RealType,
|
|
// others requires static cast to RealType from long double.
|
|
|
|
if(std::numeric_limits<RealType>::has_quiet_NaN)
|
|
{
|
|
// Mean
|
|
BOOST_CHECK((boost::math::isnan)(mean(ignore_error_non_central_t(-nan, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(mean(ignore_error_non_central_t(+nan, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(mean(ignore_error_non_central_t(-1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(mean(ignore_error_non_central_t(0, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(mean(ignore_error_non_central_t(1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(mean(ignore_error_non_central_t(2, nan))));
|
|
BOOST_CHECK((boost::math::isnan)(mean(ignore_error_non_central_t(nan, nan))));
|
|
BOOST_CHECK(boost::math::isfinite(mean(ignore_error_non_central_t(2, 0)))); // OK
|
|
|
|
// Variance
|
|
BOOST_CHECK((boost::math::isnan)(variance(ignore_error_non_central_t(nan, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(variance(ignore_error_non_central_t(1, nan))));
|
|
BOOST_CHECK((boost::math::isnan)(variance(ignore_error_non_central_t(2, nan))));
|
|
BOOST_CHECK((boost::math::isnan)(variance(ignore_error_non_central_t(-1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(variance(ignore_error_non_central_t(0, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(variance(ignore_error_non_central_t(1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(variance(ignore_error_non_central_t(static_cast<RealType>(1.7L), 0))));
|
|
BOOST_CHECK((boost::math::isnan)(variance(ignore_error_non_central_t(2, 0))));
|
|
|
|
// Skewness
|
|
BOOST_CHECK((boost::math::isnan)(skewness(ignore_error_non_central_t(std::numeric_limits<RealType>::quiet_NaN(), 0))));
|
|
BOOST_CHECK((boost::math::isnan)(skewness(ignore_error_non_central_t(-1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(skewness(ignore_error_non_central_t(0, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(skewness(ignore_error_non_central_t(1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(skewness(ignore_error_non_central_t(2, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(skewness(ignore_error_non_central_t(3, 0))));
|
|
|
|
// Kurtosis
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis(ignore_error_non_central_t(std::numeric_limits<RealType>::quiet_NaN(), 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis(ignore_error_non_central_t(-1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis(ignore_error_non_central_t(0, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis(ignore_error_non_central_t(1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis(ignore_error_non_central_t(2, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis(ignore_error_non_central_t(static_cast<RealType>(2.0001L), 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis(ignore_error_non_central_t(3, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis(ignore_error_non_central_t(4, 0))));
|
|
|
|
// Kurtosis excess
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis_excess(ignore_error_non_central_t(std::numeric_limits<RealType>::quiet_NaN(), 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis_excess(ignore_error_non_central_t(-1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis_excess(ignore_error_non_central_t(0, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis_excess(ignore_error_non_central_t(1, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis_excess(ignore_error_non_central_t(2, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis_excess(ignore_error_non_central_t(static_cast<RealType>(2.0001L), 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis_excess(ignore_error_non_central_t(3, 0))));
|
|
BOOST_CHECK((boost::math::isnan)(kurtosis_excess(ignore_error_non_central_t(4, 0))));
|
|
} // has_quiet_NaN
|
|
BOOST_CHECK(boost::math::isfinite(mean(ignore_error_non_central_t(1 + std::numeric_limits<RealType>::epsilon(), 0))));
|
|
BOOST_CHECK(boost::math::isfinite(variance(ignore_error_non_central_t(2 + 2 * std::numeric_limits<RealType>::epsilon(), 0))));
|
|
BOOST_CHECK(boost::math::isfinite(variance(ignore_error_non_central_t(static_cast<RealType>(2.0001L), 0))));
|
|
BOOST_CHECK(boost::math::isfinite(variance(ignore_error_non_central_t(2 + 2 * std::numeric_limits<RealType>::epsilon(), 0))));
|
|
BOOST_CHECK(boost::math::isfinite(skewness(ignore_error_non_central_t(3 + 3 * std::numeric_limits<RealType>::epsilon(), 0))));
|
|
BOOST_CHECK(boost::math::isfinite(kurtosis(ignore_error_non_central_t(4 + 4 * std::numeric_limits<RealType>::epsilon(), 0))));
|
|
BOOST_CHECK(boost::math::isfinite(kurtosis(ignore_error_non_central_t(static_cast<RealType>(4.0001L), 0))));
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// check_out_of_range<non_central_t_distribution<RealType> >(1, 0); // Fails one check because allows df = infinity.
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check_support<non_central_t_distribution<RealType> >(non_central_t_distribution<RealType>(1, 0));
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} // ordinary floats.
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} // template <class RealType> void test_ignore_policy(RealType)
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