// boost\math\distributions\beta.hpp // Copyright John Maddock 2006. // Copyright Paul A. Bristow 2006. // 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/Beta_distribution // http://www.itl.nist.gov/div898/handbook/eda/section3/eda366h.htm // http://mathworld.wolfram.com/BetaDistribution.html // The Beta Distribution is a continuous probability distribution. // The beta distribution is used to model events which are constrained to take place // within an interval defined by maxima and minima, // so is used extensively in PERT and other project management systems // to describe the time to completion. // The cdf of the beta distribution is used as a convenient way // of obtaining the sum over a set of binomial outcomes. // The beta distribution is also used in Bayesian statistics. #ifndef BOOST_MATH_DIST_BETA_HPP #define BOOST_MATH_DIST_BETA_HPP #include #include // for beta. #include // complements. #include // error checks #include // isnan. #include // for root finding. #if defined (BOOST_MSVC) # pragma warning(push) # pragma warning(disable: 4702) // unreachable code // in domain_error_imp in error_handling #endif #include namespace boost { namespace math { namespace beta_detail { // Common error checking routines for beta distribution functions: template inline bool check_alpha(const char* function, const RealType& alpha, RealType* result, const Policy& pol) { if(!(boost::math::isfinite)(alpha) || (alpha <= 0)) { *result = policies::raise_domain_error( function, "Alpha argument is %1%, but must be > 0 !", alpha, pol); return false; } return true; } // bool check_alpha template inline bool check_beta(const char* function, const RealType& beta, RealType* result, const Policy& pol) { if(!(boost::math::isfinite)(beta) || (beta <= 0)) { *result = policies::raise_domain_error( function, "Beta argument is %1%, but must be > 0 !", beta, pol); return false; } return true; } // bool check_beta template inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol) { if((p < 0) || (p > 1) || !(boost::math::isfinite)(p)) { *result = policies::raise_domain_error( function, "Probability argument is %1%, but must be >= 0 and <= 1 !", p, pol); return false; } return true; } // bool check_prob template inline bool check_x(const char* function, const RealType& x, RealType* result, const Policy& pol) { if(!(boost::math::isfinite)(x) || (x < 0) || (x > 1)) { *result = policies::raise_domain_error( function, "x argument is %1%, but must be >= 0 and <= 1 !", x, pol); return false; } return true; } // bool check_x template inline bool check_dist(const char* function, const RealType& alpha, const RealType& beta, RealType* result, const Policy& pol) { // Check both alpha and beta. return check_alpha(function, alpha, result, pol) && check_beta(function, beta, result, pol); } // bool check_dist template inline bool check_dist_and_x(const char* function, const RealType& alpha, const RealType& beta, RealType x, RealType* result, const Policy& pol) { return check_dist(function, alpha, beta, result, pol) && beta_detail::check_x(function, x, result, pol); } // bool check_dist_and_x template inline bool check_dist_and_prob(const char* function, const RealType& alpha, const RealType& beta, RealType p, RealType* result, const Policy& pol) { return check_dist(function, alpha, beta, result, pol) && check_prob(function, p, result, pol); } // bool check_dist_and_prob template inline bool check_mean(const char* function, const RealType& mean, RealType* result, const Policy& pol) { if(!(boost::math::isfinite)(mean) || (mean <= 0)) { *result = policies::raise_domain_error( function, "mean argument is %1%, but must be > 0 !", mean, pol); return false; } return true; } // bool check_mean template inline bool check_variance(const char* function, const RealType& variance, RealType* result, const Policy& pol) { if(!(boost::math::isfinite)(variance) || (variance <= 0)) { *result = policies::raise_domain_error( function, "variance argument is %1%, but must be > 0 !", variance, pol); return false; } return true; } // bool check_variance } // namespace beta_detail // typedef beta_distribution beta; // is deliberately NOT included to avoid a name clash with the beta function. // Use beta_distribution<> mybeta(...) to construct type double. template > class beta_distribution { public: typedef RealType value_type; typedef Policy policy_type; beta_distribution(RealType l_alpha = 1, RealType l_beta = 1) : m_alpha(l_alpha), m_beta(l_beta) { RealType result; beta_detail::check_dist( "boost::math::beta_distribution<%1%>::beta_distribution", m_alpha, m_beta, &result, Policy()); } // beta_distribution constructor. // Accessor functions: RealType alpha() const { return m_alpha; } RealType beta() const { // . return m_beta; } // Estimation of the alpha & beta parameters. // http://en.wikipedia.org/wiki/Beta_distribution // gives formulae in section on parameter estimation. // Also NIST EDA page 3 & 4 give the same. // http://www.itl.nist.gov/div898/handbook/eda/section3/eda366h.htm // http://www.epi.ucdavis.edu/diagnostictests/betabuster.html static RealType find_alpha( RealType mean, // Expected value of mean. RealType variance) // Expected value of variance. { static const char* function = "boost::math::beta_distribution<%1%>::find_alpha"; RealType result = 0; // of error checks. if(false == ( beta_detail::check_mean(function, mean, &result, Policy()) && beta_detail::check_variance(function, variance, &result, Policy()) ) ) { return result; } return mean * (( (mean * (1 - mean)) / variance)- 1); } // RealType find_alpha static RealType find_beta( RealType mean, // Expected value of mean. RealType variance) // Expected value of variance. { static const char* function = "boost::math::beta_distribution<%1%>::find_beta"; RealType result = 0; // of error checks. if(false == ( beta_detail::check_mean(function, mean, &result, Policy()) && beta_detail::check_variance(function, variance, &result, Policy()) ) ) { return result; } return (1 - mean) * (((mean * (1 - mean)) /variance)-1); } // RealType find_beta // Estimate alpha & beta from either alpha or beta, and x and probability. // Uses for these parameter estimators are unclear. static RealType find_alpha( RealType beta, // from beta. RealType x, // x. RealType probability) // cdf { static const char* function = "boost::math::beta_distribution<%1%>::find_alpha"; RealType result = 0; // of error checks. if(false == ( beta_detail::check_prob(function, probability, &result, Policy()) && beta_detail::check_beta(function, beta, &result, Policy()) && beta_detail::check_x(function, x, &result, Policy()) ) ) { return result; } return ibeta_inva(beta, x, probability, Policy()); } // RealType find_alpha(beta, a, probability) static RealType find_beta( // ibeta_invb(T b, T x, T p); (alpha, x, cdf,) RealType alpha, // alpha. RealType x, // probability x. RealType probability) // probability cdf. { static const char* function = "boost::math::beta_distribution<%1%>::find_beta"; RealType result = 0; // of error checks. if(false == ( beta_detail::check_prob(function, probability, &result, Policy()) && beta_detail::check_alpha(function, alpha, &result, Policy()) && beta_detail::check_x(function, x, &result, Policy()) ) ) { return result; } return ibeta_invb(alpha, x, probability, Policy()); } // RealType find_beta(alpha, x, probability) private: RealType m_alpha; // Two parameters of the beta distribution. RealType m_beta; }; // template class beta_distribution template inline const std::pair range(const beta_distribution& /* dist */) { // Range of permissible values for random variable x. using boost::math::tools::max_value; return std::pair(static_cast(0), static_cast(1)); } template inline const std::pair support(const beta_distribution& /* dist */) { // Range of supported values for random variable x. // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero. return std::pair(static_cast(0), static_cast(1)); } template inline RealType mean(const beta_distribution& dist) { // Mean of beta distribution = np. return dist.alpha() / (dist.alpha() + dist.beta()); } // mean template inline RealType variance(const beta_distribution& dist) { // Variance of beta distribution = np(1-p). RealType a = dist.alpha(); RealType b = dist.beta(); return (a * b) / ((a + b ) * (a + b) * (a + b + 1)); } // variance template inline RealType mode(const beta_distribution& dist) { static const char* function = "boost::math::mode(beta_distribution<%1%> const&)"; RealType result; if ((dist.alpha() <= 1)) { result = policies::raise_domain_error( function, "mode undefined for alpha = %1%, must be > 1!", dist.alpha(), Policy()); return result; } if ((dist.beta() <= 1)) { result = policies::raise_domain_error( function, "mode undefined for beta = %1%, must be > 1!", dist.beta(), Policy()); return result; } RealType a = dist.alpha(); RealType b = dist.beta(); return (a-1) / (a + b - 2); } // mode //template //inline RealType median(const beta_distribution& dist) //{ // Median of beta distribution is not defined. // return tools::domain_error(function, "Median is not implemented, result is %1%!", std::numeric_limits::quiet_NaN()); //} // median //But WILL be provided by the derived accessor as quantile(0.5). template inline RealType skewness(const beta_distribution& dist) { BOOST_MATH_STD_USING // ADL of std functions. RealType a = dist.alpha(); RealType b = dist.beta(); return (2 * (b-a) * sqrt(a + b + 1)) / ((a + b + 2) * sqrt(a * b)); } // skewness template inline RealType kurtosis_excess(const beta_distribution& dist) { RealType a = dist.alpha(); RealType b = dist.beta(); RealType a_2 = a * a; RealType n = 6 * (a_2 * a - a_2 * (2 * b - 1) + b * b * (b + 1) - 2 * a * b * (b + 2)); RealType d = a * b * (a + b + 2) * (a + b + 3); return n / d; } // kurtosis_excess template inline RealType kurtosis(const beta_distribution& dist) { return 3 + kurtosis_excess(dist); } // kurtosis template inline RealType pdf(const beta_distribution& dist, const RealType& x) { // Probability Density/Mass Function. BOOST_FPU_EXCEPTION_GUARD static const char* function = "boost::math::pdf(beta_distribution<%1%> const&, %1%)"; BOOST_MATH_STD_USING // for ADL of std functions RealType a = dist.alpha(); RealType b = dist.beta(); // Argument checks: RealType result = 0; if(false == beta_detail::check_dist_and_x( function, a, b, x, &result, Policy())) { return result; } using boost::math::beta; return ibeta_derivative(a, b, x, Policy()); } // pdf template inline RealType cdf(const beta_distribution& dist, const RealType& x) { // Cumulative Distribution Function beta. BOOST_MATH_STD_USING // for ADL of std functions static const char* function = "boost::math::cdf(beta_distribution<%1%> const&, %1%)"; RealType a = dist.alpha(); RealType b = dist.beta(); // Argument checks: RealType result = 0; if(false == beta_detail::check_dist_and_x( function, a, b, x, &result, Policy())) { return result; } // Special cases: if (x == 0) { return 0; } else if (x == 1) { return 1; } return ibeta(a, b, x, Policy()); } // beta cdf template inline RealType cdf(const complemented2_type, RealType>& c) { // Complemented Cumulative Distribution Function beta. BOOST_MATH_STD_USING // for ADL of std functions static const char* function = "boost::math::cdf(beta_distribution<%1%> const&, %1%)"; RealType const& x = c.param; beta_distribution const& dist = c.dist; RealType a = dist.alpha(); RealType b = dist.beta(); // Argument checks: RealType result = 0; if(false == beta_detail::check_dist_and_x( function, a, b, x, &result, Policy())) { return result; } if (x == 0) { return 1; } else if (x == 1) { return 0; } // Calculate cdf beta using the incomplete beta function. // Use of ibeta here prevents cancellation errors in calculating // 1 - x if x is very small, perhaps smaller than machine epsilon. return ibetac(a, b, x, Policy()); } // beta cdf template inline RealType quantile(const beta_distribution& dist, const RealType& p) { // Quantile or Percent Point beta function or // Inverse Cumulative probability distribution function CDF. // Return x (0 <= x <= 1), // for a given probability p (0 <= p <= 1). // These functions take a probability as an argument // and return a value such that the probability that a random variable x // will be less than or equal to that value // is whatever probability you supplied as an argument. static const char* function = "boost::math::quantile(beta_distribution<%1%> const&, %1%)"; RealType result = 0; // of argument checks: RealType a = dist.alpha(); RealType b = dist.beta(); if(false == beta_detail::check_dist_and_prob( function, a, b, p, &result, Policy())) { return result; } // Special cases: if (p == 0) { return 0; } if (p == 1) { return 1; } return ibeta_inv(a, b, p, static_cast(0), Policy()); } // quantile template inline RealType quantile(const complemented2_type, RealType>& c) { // Complement Quantile or Percent Point beta function . // Return the number of expected x for a given // complement of the probability q. static const char* function = "boost::math::quantile(beta_distribution<%1%> const&, %1%)"; // // Error checks: RealType q = c.param; const beta_distribution& dist = c.dist; RealType result = 0; RealType a = dist.alpha(); RealType b = dist.beta(); if(false == beta_detail::check_dist_and_prob( function, a, b, q, &result, Policy())) { return result; } // Special cases: if(q == 1) { return 0; } if(q == 0) { return 1; } return ibetac_inv(a, b, q, static_cast(0), Policy()); } // Quantile Complement } // 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 #if defined (BOOST_MSVC) # pragma warning(pop) #endif #endif // BOOST_MATH_DIST_BETA_HPP