util.hpp File Reference

#include <cmath>
#include <iomanip>
#include <iostream>
#include <vector>
#include <stan/math/matrix/Eigen.hpp>
#include <stan/agrad/rev/matrix/grad.hpp>
#include <stan/agrad/rev/var.hpp>
#include <stan/agrad/autodiff.hpp>

Go to the source code of this file.

Classes
struct	stan::model::model_functional< M >

Namespaces
	stan
	Probability, optimization and sampling library.
	stan::model
	For compiling models.

Functions
template<bool jacobian_adjust_transform, class M >
double	stan::model::log_prob_propto (const M &model, std::vector< double > &params_r, std::vector< int > &params_i, std::ostream *msgs=0)
	Helper function to calculate log probability for double scalars up to a proportion. More...
template<bool propto, bool jacobian_adjust_transform, class M >
double	stan::model::log_prob_grad (const M &model, std::vector< double > &params_r, std::vector< int > &params_i, std::vector< double > &gradient, std::ostream *msgs=0)
	Compute the gradient using reverse-mode automatic differentiation, writing the result into the specified gradient, using the specified perturbation. More...
template<bool jacobian_adjust_transform, class M >
double	stan::model::log_prob_propto (const M &model, Eigen::VectorXd &params_r, std::ostream *msgs=0)
	Helper function to calculate log probability for double scalars up to a proportion. More...
template<bool propto, bool jacobian_adjust_transform, class M >
double	stan::model::log_prob_grad (const M &model, Eigen::VectorXd &params_r, Eigen::VectorXd &gradient, std::ostream *msgs=0)
	Compute the gradient using reverse-mode automatic differentiation, writing the result into the specified gradient, using the specified perturbation. More...
template<bool propto, bool jacobian_adjust_transform, class M >
void	stan::model::finite_diff_grad (const M &model, std::vector< double > &params_r, std::vector< int > &params_i, std::vector< double > &grad, double epsilon=1e-6, std::ostream *msgs=0)
	Compute the gradient using finite differences for the specified parameters, writing the result into the specified gradient, using the specified perturbation. More...
template<bool propto, bool jacobian_adjust_transform, class M >
int	stan::model::test_gradients (const M &model, std::vector< double > &params_r, std::vector< int > &params_i, double epsilon=1e-6, double error=1e-6, std::ostream &o=std::cout, std::ostream *msgs=0)
	Test the log_prob_grad() function's ability to produce accurate gradients using finite differences. More...
template<bool propto, bool jacobian_adjust_transform, class M >
double	stan::model::grad_hess_log_prob (const M &model, std::vector< double > &params_r, std::vector< int > &params_i, std::vector< double > &gradient, std::vector< double > &hessian, std::ostream *msgs=0)
	Evaluate the log-probability, its gradient, and its Hessian at params_r. More...
template<class M >
void	stan::model::gradient (const M &model, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &f, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad_f, std::ostream *msgs=0)
template<class M >
void	stan::model::hessian (const M &model, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, double &f, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad_f, Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &hess_f, std::ostream *msgs=0)
template<class M >
void	stan::model::gradient_dot_vector (const M &model, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &v, double &f, double &grad_f_dot_v, std::ostream *msgs=0)
template<class M >
void	stan::model::hessian_times_vector (const M &model, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &v, double &f, Eigen::Matrix< double, Eigen::Dynamic, 1 > &hess_f_dot_v, std::ostream *msgs=0)
template<class M >
void	stan::model::grad_tr_mat_times_hessian (const M &model, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &x, const Eigen::Matrix< double, Eigen::Dynamic, Eigen::Dynamic > &X, Eigen::Matrix< double, Eigen::Dynamic, 1 > &grad_tr_X_hess_f, std::ostream *msgs=0)