123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502 |
- // test_nc_t.cpp
- // Copyright John Maddock 2008, 2012.
- // Copyright Paul A. Bristow 2012.
- // 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)
- #include <pch.hpp> // Need to include lib/math/test in path.
- #ifdef _MSC_VER
- #pragma warning (disable:4127 4512)
- #endif
- #if !defined(TEST_FLOAT) && !defined(TEST_DOUBLE) && !defined(TEST_LDOUBLE) && !defined(TEST_REAL_CONCEPT)
- # define TEST_FLOAT
- # define TEST_DOUBLE
- # define TEST_LDOUBLE
- # define TEST_REAL_CONCEPT
- #endif
- #include <boost/math/tools/test.hpp>
- #include <boost/math/concepts/real_concept.hpp> // for real_concept
- #include <boost/math/distributions/non_central_t.hpp> // for chi_squared_distribution.
- #include <boost/math/distributions/normal.hpp> // for normal distribution (for comparison).
- #define BOOST_TEST_MAIN
- #include <boost/test/unit_test.hpp> // for test_main
- #include <boost/test/results_collector.hpp>
- #include <boost/test/unit_test.hpp>
- #include <boost/test/tools/floating_point_comparison.hpp> // for BOOST_CHECK_CLOSE
- #include "functor.hpp"
- #include "handle_test_result.hpp"
- #include "table_type.hpp"
- #include "test_nc_t.hpp"
- #include <iostream>
- #include <iomanip>
- using std::cout;
- using std::endl;
- #include <limits>
- using std::numeric_limits;
- void expected_results()
- {
- //
- // Define the max and mean errors expected for
- // various compilers and platforms.
- //
- const char* largest_type;
- #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
- if(boost::math::policies::digits<double, boost::math::policies::policy<> >() == boost::math::policies::digits<long double, boost::math::policies::policy<> >())
- {
- largest_type = "(long\\s+)?double|real_concept";
- }
- else
- {
- largest_type = "long double|real_concept";
- }
- #else
- largest_type = "(long\\s+)?double|real_concept";
- #endif
- //
- // Catch all cases come last:
- //
- if(std::numeric_limits<long double>::digits > 54)
- {
- add_expected_result(
- "[^|]*", // compiler
- "[^|]*", // stdlib
- "[^|]*", // platform
- largest_type, // test type(s)
- "[^|]*large[^|]*", // test data group
- "[^|]*", 2000000, 200000); // test function
- add_expected_result(
- "[^|]*", // compiler
- "[^|]*", // stdlib
- "[^|]*", // platform
- "double", // test type(s)
- "[^|]*large[^|]*", // test data group
- "[^|]*", 500, 100); // test function
- }
- add_expected_result(
- "[^|]*", // compiler
- "[^|]*", // stdlib
- "[^|]*", // platform
- "real_concept", // test type(s)
- "[^|]*", // test data group
- "[^|]*", 300000, 100000); // test function
- add_expected_result(
- "[^|]*", // compiler
- "[^|]*", // stdlib
- "[^|]*", // platform
- largest_type, // test type(s)
- "[^|]*large[^|]*", // test data group
- "[^|]*", 1500, 300); // test function
- add_expected_result(
- "[^|]*", // compiler
- "[^|]*", // stdlib
- "[^|]*", // platform
- largest_type, // test type(s)
- "[^|]*small[^|]*", // test data group
- "[^|]*", 400, 100); // test function
- add_expected_result(
- "[^|]*", // compiler
- "[^|]*", // stdlib
- ".*Solaris.*", // platform
- largest_type, // test type(s)
- "[^|]*", // test data group
- "[^|]*", 400, 100); // test function
- add_expected_result(
- "[^|]*", // compiler
- "[^|]*", // stdlib
- "[^|]*", // platform
- largest_type, // test type(s)
- "[^|]*", // test data group
- "[^|]*", 250, 50); // test function
- //
- // Finish off by printing out the compiler/stdlib/platform names,
- // we do this to make it easier to mark up expected error rates.
- //
- std::cout << "Tests run with " << BOOST_COMPILER << ", "
- << BOOST_STDLIB << ", " << BOOST_PLATFORM << std::endl;
- }
- BOOST_AUTO_TEST_CASE( test_main )
- {
- BOOST_MATH_CONTROL_FP;
- // Basic sanity-check spot values.
- expected_results();
- // (Parameter value, arbitrarily zero, only communicates the floating point type).
- #ifdef TEST_FLOAT
- test_spots(0.0F); // Test float.
- #endif
- #ifdef TEST_DOUBLE
- test_spots(0.0); // Test double.
- #endif
- #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
- #ifdef TEST_LDOUBLE
- test_spots(0.0L); // Test long double.
- #endif
- #ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
- #ifdef TEST_REAL_CONCEPT
- test_spots(boost::math::concepts::real_concept(0.)); // Test real concept.
- #endif
- #endif
- #endif
-
- #ifdef TEST_FLOAT
- test_accuracy(0.0F, "float"); // Test float.
- test_big_df(0.F); // float
- #endif
- #ifdef TEST_DOUBLE
- test_accuracy(0.0, "double"); // Test double.
- test_big_df(0.); // double
- test_ignore_policy(0.0);
- #endif
- #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
- #ifdef TEST_LDOUBLE
- test_accuracy(0.0L, "long double"); // Test long double.
- #endif
- #ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
- #ifdef TEST_REAL_CONCEPT
- test_accuracy(boost::math::concepts::real_concept(0.), "real_concept"); // Test real concept.
- #endif
- #endif
- #endif
- /* */
-
- } // BOOST_AUTO_TEST_CASE( test_main )
- /*
- Output:
- Description: Autorun "J:\Cpp\MathToolkit\test\Math_test\Debug\test_nc_t.exe"
- Running 1 test case...
- Tests run with Microsoft Visual C++ version 10.0, Dinkumware standard library version 520, Win32
- Tolerance = 0.000596046%.
- Tolerance = 5e-010%.
- Tolerance = 5e-010%.
- Tolerance = 1e-008%.
- Testing: Non Central T
- CDF<float> Max = 0 RMS Mean=0
-
- CCDF<float> Max = 0 RMS Mean=0
-
-
- Testing: float quantile sanity check, with tests Non Central T
- Testing: Non Central T (small non-centrality)
- CDF<float> Max = 0 RMS Mean=0
-
- CCDF<float> Max = 0 RMS Mean=0
-
-
- Testing: float quantile sanity check, with tests Non Central T (small non-centrality)
- Testing: Non Central T (large parameters)
- CDF<float> Max = 0 RMS Mean=0
-
- CCDF<float> Max = 0 RMS Mean=0
-
-
- Testing: float quantile sanity check, with tests Non Central T (large parameters)
- Testing: Non Central T
- CDF<double> Max = 137.7 RMS Mean=31.5
- worst case at row: 181
- { 188.01481628417969, -282.022216796875, -298.02532958984375, 0.1552789395983287, 0.84472106040167128 }
-
- CCDF<double> Max = 150.4 RMS Mean=32.32
- worst case at row: 184
- { 191.43339538574219, 765.73358154296875, 820.14422607421875, 0.89943076553533785, 0.10056923446466212 }
-
-
- Testing: double quantile sanity check, with tests Non Central T
- Testing: Non Central T (small non-centrality)
- CDF<double> Max = 3.605 RMS Mean=1.031
- worst case at row: 42
- { 7376104448, 7.3761043495323975e-007, -1.3614851236343384, 0.086680099352107118, 0.91331990064789292 }
-
- CCDF<double> Max = 5.207 RMS Mean=1.432
- worst case at row: 38
- { 1524088576, 1.5240885886669275e-007, 1.3784774541854858, 0.91597201432644526, 0.084027985673554725 }
-
-
- Testing: double quantile sanity check, with tests Non Central T (small non-centrality)
- Testing: Non Central T (large parameters)
- CDF<double> Max = 286.4 RMS Mean=62.79
- worst case at row: 24
- { 1.3091821180254421e+019, 1309.18212890625, 1308.01171875, 0.12091797523015677, 0.87908202476984321 }
-
- CCDF<double> Max = 226.9 RMS Mean=50.41
- worst case at row: 23
- { 7.9217674231144776e+018, 792.1767578125, 793.54827880859375, 0.91489369852628, 0.085106301473719961 }
-
-
- Testing: double quantile sanity check, with tests Non Central T (large parameters)
- Testing: Non Central T
- CDF<long double> Max = 137.7 RMS Mean=31.5
- worst case at row: 181
- { 188.01481628417969, -282.022216796875, -298.02532958984375, 0.1552789395983287, 0.84472106040167128 }
-
- CCDF<long double> Max = 150.4 RMS Mean=32.32
- worst case at row: 184
- { 191.43339538574219, 765.73358154296875, 820.14422607421875, 0.89943076553533785, 0.10056923446466212 }
-
-
- Testing: long double quantile sanity check, with tests Non Central T
- Testing: Non Central T (small non-centrality)
- CDF<long double> Max = 3.605 RMS Mean=1.031
- worst case at row: 42
- { 7376104448, 7.3761043495323975e-007, -1.3614851236343384, 0.086680099352107118, 0.91331990064789292 }
-
- CCDF<long double> Max = 5.207 RMS Mean=1.432
- worst case at row: 38
- { 1524088576, 1.5240885886669275e-007, 1.3784774541854858, 0.91597201432644526, 0.084027985673554725 }
-
-
- Testing: long double quantile sanity check, with tests Non Central T (small non-centrality)
- Testing: Non Central T (large parameters)
- CDF<long double> Max = 286.4 RMS Mean=62.79
- worst case at row: 24
- { 1.3091821180254421e+019, 1309.18212890625, 1308.01171875, 0.12091797523015677, 0.87908202476984321 }
-
- CCDF<long double> Max = 226.9 RMS Mean=50.41
- worst case at row: 23
- { 7.9217674231144776e+018, 792.1767578125, 793.54827880859375, 0.91489369852628, 0.085106301473719961 }
-
-
- Testing: long double quantile sanity check, with tests Non Central T (large parameters)
- Testing: Non Central T
- CDF<real_concept> Max = 2.816e+005 RMS Mean=2.029e+004
- worst case at row: 185
- { 191.50137329101562, -957.5068359375, -1035.4078369140625, 0.072545502958829097, 0.92745449704117089 }
-
- CCDF<real_concept> Max = 1.304e+005 RMS Mean=1.529e+004
- worst case at row: 184
- { 191.43339538574219, 765.73358154296875, 820.14422607421875, 0.89943076553533785, 0.10056923446466212 }
-
-
- cdf(n10, 11) = 0.84134471416473389 0.15865525603294373
- cdf(n10, 9) = 0.15865525603294373 0.84134471416473389
- cdf(maxdf10, 11) = 0.84134477376937866 0.15865525603294373
- cdf(infdf10, 11) = 0.84134477376937866 0.15865525603294373
- cdf(n10, 11) = 0.84134474606854293 0.15865525393145707
- cdf(n10, 9) = 0.15865525393145707 0.84134474606854293
- cdf(maxdf10, 11) = 0.84134474606854293 0.15865525393145707
- cdf(infdf10, 11) = 0.84134474606854293 0.15865525393145707
-
- *** No errors detected
- Description: Autorun "J:\Cpp\MathToolkit\test\Math_test\Debug\test_nc_t.exe"
- Running 1 test case...
- Tests run with Microsoft Visual C++ version 10.0, Dinkumware standard library version 520, Win32
- Tolerance = 0.000596046%.
- Tolerance = 5e-010%.
- Tolerance = 5e-010%.
- Tolerance = 1e-008%.
- Testing: Non Central T
- CDF<float> Max = 0 RMS Mean=0
-
- CCDF<float> Max = 0 RMS Mean=0
-
-
- Testing: float quantile sanity check, with tests Non Central T
- Testing: Non Central T (small non-centrality)
- CDF<float> Max = 0 RMS Mean=0
-
- CCDF<float> Max = 0 RMS Mean=0
-
-
- Testing: float quantile sanity check, with tests Non Central T (small non-centrality)
- Testing: Non Central T (large parameters)
- CDF<float> Max = 0 RMS Mean=0
-
- CCDF<float> Max = 0 RMS Mean=0
-
-
- Testing: float quantile sanity check, with tests Non Central T (large parameters)
- Testing: Non Central T
- CDF<double> Max = 137.7 RMS Mean=31.5
- worst case at row: 181
- { 188.01481628417969, -282.022216796875, -298.02532958984375, 0.1552789395983287, 0.84472106040167128 }
-
- CCDF<double> Max = 150.4 RMS Mean=32.32
- worst case at row: 184
- { 191.43339538574219, 765.73358154296875, 820.14422607421875, 0.89943076553533785, 0.10056923446466212 }
-
-
- Testing: double quantile sanity check, with tests Non Central T
- Testing: Non Central T (small non-centrality)
- CDF<double> Max = 3.605 RMS Mean=1.031
- worst case at row: 42
- { 7376104448, 7.3761043495323975e-007, -1.3614851236343384, 0.086680099352107118, 0.91331990064789292 }
-
- CCDF<double> Max = 5.207 RMS Mean=1.432
- worst case at row: 38
- { 1524088576, 1.5240885886669275e-007, 1.3784774541854858, 0.91597201432644526, 0.084027985673554725 }
-
-
- Testing: double quantile sanity check, with tests Non Central T (small non-centrality)
- Testing: Non Central T (large parameters)
- CDF<double> Max = 286.4 RMS Mean=62.79
- worst case at row: 24
- { 1.3091821180254421e+019, 1309.18212890625, 1308.01171875, 0.12091797523015677, 0.87908202476984321 }
-
- CCDF<double> Max = 226.9 RMS Mean=50.41
- worst case at row: 23
- { 7.9217674231144776e+018, 792.1767578125, 793.54827880859375, 0.91489369852628, 0.085106301473719961 }
-
-
- Testing: double quantile sanity check, with tests Non Central T (large parameters)
- Testing: Non Central T
- CDF<long double> Max = 137.7 RMS Mean=31.5
- worst case at row: 181
- { 188.01481628417969, -282.022216796875, -298.02532958984375, 0.1552789395983287, 0.84472106040167128 }
-
- CCDF<long double> Max = 150.4 RMS Mean=32.32
- worst case at row: 184
- { 191.43339538574219, 765.73358154296875, 820.14422607421875, 0.89943076553533785, 0.10056923446466212 }
-
-
- Testing: long double quantile sanity check, with tests Non Central T
- Testing: Non Central T (small non-centrality)
- CDF<long double> Max = 3.605 RMS Mean=1.031
- worst case at row: 42
- { 7376104448, 7.3761043495323975e-007, -1.3614851236343384, 0.086680099352107118, 0.91331990064789292 }
-
- CCDF<long double> Max = 5.207 RMS Mean=1.432
- worst case at row: 38
- { 1524088576, 1.5240885886669275e-007, 1.3784774541854858, 0.91597201432644526, 0.084027985673554725 }
-
-
- Testing: long double quantile sanity check, with tests Non Central T (small non-centrality)
- Testing: Non Central T (large parameters)
- CDF<long double> Max = 286.4 RMS Mean=62.79
- worst case at row: 24
- { 1.3091821180254421e+019, 1309.18212890625, 1308.01171875, 0.12091797523015677, 0.87908202476984321 }
-
- CCDF<long double> Max = 226.9 RMS Mean=50.41
- worst case at row: 23
- { 7.9217674231144776e+018, 792.1767578125, 793.54827880859375, 0.91489369852628, 0.085106301473719961 }
-
-
- Testing: long double quantile sanity check, with tests Non Central T (large parameters)
- Testing: Non Central T
- CDF<real_concept> Max = 2.816e+005 RMS Mean=2.029e+004
- worst case at row: 185
- { 191.50137329101562, -957.5068359375, -1035.4078369140625, 0.072545502958829097, 0.92745449704117089 }
-
- CCDF<real_concept> Max = 1.304e+005 RMS Mean=1.529e+004
- worst case at row: 184
- { 191.43339538574219, 765.73358154296875, 820.14422607421875, 0.89943076553533785, 0.10056923446466212 }
-
-
-
- *** No errors detected
- */
- /*
- Temporary stuff from student's t version.
- // Calculate 1 / eps, the point where student's t should change to normal distribution.
- RealType limit = 1 / boost::math::tools::epsilon<RealType>();
- using namespace boost::math::policies;
- typedef policy<digits10<17> > accurate_policy; // 17 = max_digits10 where available.
- limit = 1 / policies::get_epsilon<RealType, accurate_policy>();
- BOOST_CHECK_CLOSE_FRACTION(limit, static_cast<RealType>(1) / std::numeric_limits<RealType>::epsilon(), tolerance);
- // Default policy to get full accuracy.
- // std::cout << "Switch over to normal if df > " << limit << std::endl;
- // float Switch over to normal if df > 8.38861e+006
- // double Switch over to normal if df > 4.5036e+015
- // Can't test real_concept - doesn't converge.
- boost::math::normal_distribution<RealType> n01(0, 1); //
- boost::math::normal_distribution<RealType> n10(10, 1); //
- non_central_t_distribution<RealType> nct(boost::math::tools::max_value<RealType>(), 0); // Well over the switchover point,
- non_central_t_distribution<RealType> nct2(limit /5, 0); // Just below the switchover point,
- non_central_t_distribution<RealType> nct3(limit /100, 0); // Well below the switchover point,
- non_central_t_distribution<RealType> nct4(limit, 10); // Well below the switchover point, and 10 non-centrality.
- // PDF
- BOOST_CHECK_CLOSE_FRACTION(pdf(nct, 0), pdf(n01, 0.), tolerance); // normal and non-central t should be nearly equal.
- BOOST_CHECK_CLOSE_FRACTION(pdf(nct2, 0), pdf(n01, 0.), tolerance); // should be very close to normal.
- BOOST_CHECK_CLOSE_FRACTION(pdf(nct3, 0), pdf(n01, 0.), tolerance * 10); // should be close to normal.
- // BOOST_CHECK_CLOSE_FRACTION(pdf(nct4, 10), pdf(n10, 0.), tolerance * 100); // should be fairly close to normal tolerance.
- RealType delta = 10; // non-centrality.
- RealType nu = static_cast<RealType>(limit); // df
- boost::math::normal_distribution<RealType> nl(delta, 1); // Normal distribution that nct tends to for big df.
- non_central_t_distribution<RealType> nct5(nu, delta); //
- RealType x = delta;
- // BOOST_CHECK_CLOSE_FRACTION(pdf(nct5, x), pdf(nl, x), tolerance * 10 ); // nu = 1e15
- // BOOST_CHECK_CLOSE_FRACTION(pdf(nct5, x), pdf(nl, x), tolerance * 1000 ); // nu = 1e14
- // BOOST_CHECK_CLOSE_FRACTION(pdf(nct5, x), pdf(nl, x), tolerance * 10000 ); // nu = 1e13
- // BOOST_CHECK_CLOSE_FRACTION(pdf(nct5, x), pdf(nl, x), tolerance * 100000 ); // nu = 1e12
- BOOST_CHECK_CLOSE_FRACTION(pdf(nct5, x), pdf(nl, x), tolerance * 5 ); // nu = 1/eps
- // Increasing the non-centrality delta increases the difference too because increases asymmetry.
- // For example, with non-centrality = 100, need tolerance * 500
- // CDF
- BOOST_CHECK_CLOSE_FRACTION(cdf(nct, 0), cdf(n01, 0.), tolerance); // should be exactly equal.
- BOOST_CHECK_CLOSE_FRACTION(cdf(nct2, 0), cdf(n01, 0.), tolerance); // should be very close to normal.
- BOOST_CHECK_CLOSE_FRACTION(cdf(complement(n10, 11)), 1 - cdf(n10, 11), tolerance); //
- // cdf(n10, 10) = 0.841345 0.158655
- BOOST_CHECK_CLOSE_FRACTION(cdf(complement(n10, 9)), 1 - cdf(n10, 9), tolerance); //
- std::cout.precision(17);
- std::cout << "cdf(n10, 11) = " << cdf(n10, 11) << ' ' << cdf(complement(n10, 11)) << endl;
- std::cout << "cdf(n10, 9) = " << cdf(n10, 9) << ' ' << cdf(complement(n10, 9)) << endl;
- std::cout << std::numeric_limits<double>::max_digits10 << std::endl;
- std::cout.precision(17);
- using boost::math::tools::max_value;
- double eps = std::numeric_limits<double>::epsilon();
- // Use policies so that if policy requests lower precision,
- // then get the normal distribution approximation earlier.
- //limit = static_cast<double>(1) / limit; // 1/eps
- double delta = 1e2;
- double df =
- delta / (4 * eps);
- std::cout << df << std::endl; // df = 1.125899906842624e+018
-
- {
- boost::math::non_central_t_distribution<double> dist(df, delta);
- std::cout <<"mean " << mean(dist) << std::endl; // mean 1000
- std::cout <<"variance " << variance(dist) << std::endl; // variance 1
- std::cout <<"skewness " << skewness(dist) << std::endl; // skewness 8.8817841970012523e-010
- std::cout <<"kurtosis_excess " << kurtosis_excess(dist) << std::endl; // kurtosis_excess 3.0001220703125
- //1.125899906842624e+017
- //mean 100
- //variance 1
- //skewness 8.8817841970012523e-012
- //kurtosis_excess 3
- }
- */
|