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Ruta de la carpeta: \\game3dprogramming\materials\GameFactory\GameFactoryDemo\references\boost_1_35_0\boost\math\distributions\bernoulli.hpp
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// boost\math\distributions\bernoulli.hpp // Copyright John Maddock 2006. // Copyright Paul A. Bristow 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) // http://en.wikipedia.org/wiki/bernoulli_distribution // http://mathworld.wolfram.com/BernoulliDistribution.html // bernoulli distribution is the discrete probability distribution of // the number (k) of successes, in a single Bernoulli trials. // It is a version of the binomial distribution when n = 1. // But note that the bernoulli distribution // (like others including the poisson, binomial & negative binomial) // is strictly defined as a discrete function: only integral values of k are envisaged. // However because of the method of calculation using a continuous gamma function, // it is convenient to treat it as if a continous function, // and permit non-integral values of k. // To enforce the strict mathematical model, users should use floor or ceil functions // on k outside this function to ensure that k is integral. #ifndef BOOST_MATH_SPECIAL_BERNOULLI_HPP #define BOOST_MATH_SPECIAL_BERNOULLI_HPP #include
#include
#include
// complements #include
// error checks #include
// isnan. #include
namespace boost { namespace math { namespace bernoulli_detail { // Common error checking routines for bernoulli distribution functions: template
inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& /* pol */) { if(!(boost::math::isfinite)(p) || (p < 0) || (p > 1)) { *result = policies::raise_domain_error
( function, "Success fraction argument is %1%, but must be >= 0 and <= 1 !", p, Policy()); return false; } return true; } template
inline bool check_dist(const char* function, const RealType& p, RealType* result, const Policy& /* pol */) { return check_success_fraction(function, p, result, Policy()); } template
inline bool check_dist_and_k(const char* function, const RealType& p, RealType k, RealType* result, const Policy& pol) { if(check_dist(function, p, result, Policy()) == false) { return false; } if(!(boost::math::isfinite)(k) || !((k == 0) || (k == 1))) { *result = policies::raise_domain_error
( function, "Number of successes argument is %1%, but must be 0 or 1 !", k, pol); return false; } return true; } template
inline bool check_dist_and_prob(const char* function, RealType p, RealType prob, RealType* result, const Policy& /* pol */) { if(check_dist(function, p, result, Policy()) && detail::check_probability(function, prob, result, Policy()) == false) { return false; } return true; } } // namespace bernoulli_detail template
> class bernoulli_distribution { public: typedef RealType value_type; typedef Policy policy_type; bernoulli_distribution(RealType p = 0.5) : m_p(p) { // Default probability = half suits 'fair' coin tossing // where probability of heads == probability of tails. RealType result; // of checks. bernoulli_detail::check_dist( "boost::math::bernoulli_distribution<%1%>::bernoulli_distribution", m_p, &result, Policy()); } // bernoulli_distribution constructor. RealType success_fraction() const { // Probability. return m_p; } private: RealType m_p; // success_fraction }; // template
class bernoulli_distribution typedef bernoulli_distribution
bernoulli; template
inline const std::pair
range(const bernoulli_distribution
& /* dist */) { // Range of permissible values for random variable k = {0, 1}. using boost::math::tools::max_value; return std::pair
(0, 1); } template
inline const std::pair
support(const bernoulli_distribution
& /* dist */) { // Range of supported values for random variable k = {0, 1}. // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero. return std::pair
(0, 1); } template
inline RealType mean(const bernoulli_distribution
& dist) { // Mean of bernoulli distribution = p (n = 1). return dist.success_fraction(); } // mean // Rely on dereived_accessors quantile(half) //template
//inline RealType median(const bernoulli_distribution
& dist) //{ // Median of bernoulli distribution is not defined. // return tools::domain_error
(BOOST_CURRENT_FUNCTION, "Median is not implemented, result is %1%!", std::numeric_limits
::quiet_NaN()); //} // median template
inline RealType variance(const bernoulli_distribution
& dist) { // Variance of bernoulli distribution =p * q. return dist.success_fraction() * (1 - dist.success_fraction()); } // variance template
RealType pdf(const bernoulli_distribution
& dist, const RealType& k) { // Probability Density/Mass Function. BOOST_FPU_EXCEPTION_GUARD // Error check: RealType result; // of checks. if(false == bernoulli_detail::check_dist_and_k( "boost::math::pdf(bernoulli_distribution<%1%>, %1%)", dist.success_fraction(), // 0 to 1 k, // 0 or 1 &result, Policy())) { return result; } // Assume k is integral. if (k == 0) { return 1 - dist.success_fraction(); // 1 - p } else // k == 1 { return dist.success_fraction(); // p } } // pdf template
inline RealType cdf(const bernoulli_distribution
& dist, const RealType& k) { // Cumulative Distribution Function Bernoulli. RealType p = dist.success_fraction(); // Error check: RealType result; if(false == bernoulli_detail::check_dist_and_k( "boost::math::cdf(bernoulli_distribution<%1%>, %1%)", p, k, &result, Policy())) { return result; } if (k == 0) { return 1 - p; } else { // k == 1 return 1; } } // bernoulli cdf template
inline RealType cdf(const complemented2_type
, RealType>& c) { // Complemented Cumulative Distribution Function bernoulli. RealType const& k = c.param; bernoulli_distribution
const& dist = c.dist; RealType p = dist.success_fraction(); // Error checks: RealType result; if(false == bernoulli_detail::check_dist_and_k( "boost::math::cdf(bernoulli_distribution<%1%>, %1%)", p, k, &result, Policy())) { return result; } if (k == 0) { return p; } else { // k == 1 return 0; } } // bernoulli cdf complement template
inline RealType quantile(const bernoulli_distribution
& dist, const RealType& p) { // Quantile or Percent Point Bernoulli function. // Return the number of expected successes k either 0 or 1. // for a given probability p. RealType result; // of error checks: if(false == bernoulli_detail::check_dist_and_prob( "boost::math::quantile(bernoulli_distribution<%1%>, %1%)", dist.success_fraction(), p, &result, Policy())) { return result; } if (p <= (1 - dist.success_fraction())) { // p <= pdf(dist, 0) == cdf(dist, 0) return 0; } else { return 1; } } // quantile template
inline RealType quantile(const complemented2_type
, RealType>& c) { // Quantile or Percent Point bernoulli function. // Return the number of expected successes k for a given // complement of the probability q. // // Error checks: RealType q = c.param; const bernoulli_distribution
& dist = c.dist; RealType result; if(false == bernoulli_detail::check_dist_and_prob( "boost::math::quantile(bernoulli_distribution<%1%>, %1%)", dist.success_fraction(), q, &result, Policy())) { return result; } if (q <= 1 - dist.success_fraction()) { // // q <= cdf(complement(dist, 0)) == pdf(dist, 0) return 1; } else { return 0; } } // quantile complemented. template
inline RealType mode(const bernoulli_distribution
& dist) { return static_cast
((dist.success_fraction() <= 0.5) ? 0 : 1); // p = 0.5 can be 0 or 1 } template
inline RealType skewness(const bernoulli_distribution
& dist) { BOOST_MATH_STD_USING; // Aid ADL for sqrt. RealType p = dist.success_fraction(); return (1 - 2 * p) / sqrt(p * (1 - p)); } template
inline RealType kurtosis_excess(const bernoulli_distribution
& dist) { RealType p = dist.success_fraction(); // Note Wolfram says this is kurtosis in text, but gamma2 is the kurtosis excess, // and Wikipedia also says this is the kurtosis excess formula. // return (6 * p * p - 6 * p + 1) / (p * (1 - p)); // But Wolfram kurtosis article gives this simpler formula for kurtosis excess: return 1 / (1 - p) + 1/p -6; } template
inline RealType kurtosis(const bernoulli_distribution
& dist) { RealType p = dist.success_fraction(); return 1 / (1 - p) + 1/p -6 + 3; // Simpler than: // return (6 * p * p - 6 * p + 1) / (p * (1 - p)) + 3; } } // namespace math } // namespace boost // This include must be at the end, *after* the accessors // for this distribution have been defined, in order to // keep compilers that support two-phase lookup happy. #include
#endif // BOOST_MATH_SPECIAL_BERNOULLI_HPP
bernoulli.hpp
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