optimize.hpp File Reference

#include <randlib/math/constants.hpp>
#include <algorithm>
#include <cmath>
#include <concepts>
#include <functional>
#include <limits>
#include <numeric>
#include <span>
#include <tuple>
#include <vector>

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Classes
struct	randlib::math::MinimizeResult< Real >
	The MinimizeResult struct Outcome of a multivariate minimization. More...

Namespaces
namespace	randlib
namespace	randlib::math
	Beta-related functions.

Functions
template<typename RealType >
double	randlib::math::parabolicMinimum (RealType a, RealType b, RealType c, double fa, double fb, double fc)
template<typename RealType >
bool	randlib::math::findMin (const std::function< double(RealType)> &funPtr, const Triplet< RealType > &abc, double &fx, RealType &root, double epsilon)
	Combined Brent's method.
template<typename RealType >
bool	randlib::math::findMin (const std::function< double(RealType)> &funPtr, RealType closePoint, RealType &root, long double epsilon=1e-8)
	Combined Brent's method.
template<std::floating_point Real = double, class F >
MinimizeResult< Real >	randlib::math::nelderMead (const F &f, std::vector< Real > start, Real tolerance=1e-10, int maxIterations=20000)
	Downhill simplex method of Nelder and Mead with the dimension-dependent coefficients of Gao and Han (2012).
template<std::floating_point Real = double, class F >
std::vector< Real >	randlib::math::numericalGradient (const F &f, const std::vector< Real > &x)
template<std::floating_point Real = double, class F >
std::vector< std::vector< Real > >	randlib::math::numericalHessian (const F &f, const std::vector< Real > &x)
template<std::floating_point Real = double, class F >
MinimizeResult< Real >	randlib::math::bfgs (const F &f, std::vector< Real > start, Real tolerance=1e-8, int maxIterations=1000)
	Quasi-Newton minimization of Broyden, Fletcher, Goldfarb and Shanno with central-difference gradients and a backtracking line search under the Armijo condition.