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// Copyright John Maddock 2007.
// 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)
// Note that this file contains quickbook mark-up as well as code
// and comments, don't change any of the special comment mark-ups!
//[policy_eg_10
/*`
To understand how the rounding policies for
the discrete distributions can be used, we'll
use the 50-sample binomial distribution with a
success fraction of 0.5 once again, and calculate
all the possible quantiles at 0.05 and 0.95.
Begin by including the needed headers:
*/
#include <iostream>
#include <boost/math/distributions/binomial.hpp>
/*`
Next we'll bring the needed declarations into scope, and
define distribution types for all the available rounding policies:
*/
using namespace boost::math::policies;
using namespace boost::math;
typedef binomial_distribution<
double,
policy<discrete_quantile<integer_round_outwards> > >
binom_round_outwards;
typedef binomial_distribution<
double,
policy<discrete_quantile<integer_round_inwards> > >
binom_round_inwards;
typedef binomial_distribution<
double,
policy<discrete_quantile<integer_round_down> > >
binom_round_down;
typedef binomial_distribution<
double,
policy<discrete_quantile<integer_round_up> > >
binom_round_up;
typedef binomial_distribution<
double,
policy<discrete_quantile<integer_round_nearest> > >
binom_round_nearest;
typedef binomial_distribution<
double,
policy<discrete_quantile<real> > >
binom_real_quantile;
/*`
Now let's set to work calling those quantiles:
*/
int main()
{
std::cout <<
"Testing rounding policies for a 50 sample binomial distribution,\n"
"with a success fraction of 0.5.\n\n"
"Lower quantiles are calculated at p = 0.05\n\n"
"Upper quantiles at p = 0.95.\n\n";
std::cout << std::setw(25) << std::right
<< "Policy"<< std::setw(18) << std::right
<< "Lower Quantile" << std::setw(18) << std::right
<< "Upper Quantile" << std::endl;
// Test integer_round_outwards:
std::cout << std::setw(25) << std::right
<< "integer_round_outwards"
<< std::setw(18) << std::right
<< quantile(binom_round_outwards(50, 0.5), 0.05)
<< std::setw(18) << std::right
<< quantile(binom_round_outwards(50, 0.5), 0.95)
<< std::endl;
// Test integer_round_inwards:
std::cout << std::setw(25) << std::right
<< "integer_round_inwards"
<< std::setw(18) << std::right
<< quantile(binom_round_inwards(50, 0.5), 0.05)
<< std::setw(18) << std::right
<< quantile(binom_round_inwards(50, 0.5), 0.95)
<< std::endl;
// Test integer_round_down:
std::cout << std::setw(25) << std::right
<< "integer_round_down"
<< std::setw(18) << std::right
<< quantile(binom_round_down(50, 0.5), 0.05)
<< std::setw(18) << std::right
<< quantile(binom_round_down(50, 0.5), 0.95)
<< std::endl;
// Test integer_round_up:
std::cout << std::setw(25) << std::right
<< "integer_round_up"
<< std::setw(18) << std::right
<< quantile(binom_round_up(50, 0.5), 0.05)
<< std::setw(18) << std::right
<< quantile(binom_round_up(50, 0.5), 0.95)
<< std::endl;
// Test integer_round_nearest:
std::cout << std::setw(25) << std::right
<< "integer_round_nearest"
<< std::setw(18) << std::right
<< quantile(binom_round_nearest(50, 0.5), 0.05)
<< std::setw(18) << std::right
<< quantile(binom_round_nearest(50, 0.5), 0.95)
<< std::endl;
// Test real:
std::cout << std::setw(25) << std::right
<< "real"
<< std::setw(18) << std::right
<< quantile(binom_real_quantile(50, 0.5), 0.05)
<< std::setw(18) << std::right
<< quantile(binom_real_quantile(50, 0.5), 0.95)
<< std::endl;
}
/*`
Which produces the program output:
[pre
Testing rounding policies for a 50 sample binomial distribution,
with a success fraction of 0.5.
Lower quantiles are calculated at p = 0.05
Upper quantiles at p = 0.95.
Testing rounding policies for a 50 sample binomial distribution,
with a success fraction of 0.5.
Lower quantiles are calculated at p = 0.05
Upper quantiles at p = 0.95.
Policy Lower Quantile Upper Quantile
integer_round_outwards 18 31
integer_round_inwards 19 30
integer_round_down 18 30
integer_round_up 19 31
integer_round_nearest 19 30
real 18.701 30.299
]
*/
//] ends quickbook import
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