stan::math::laplace_likelihood::internal Namespace Reference

Functions
template<typename F , typename Theta , typename Stream , typename... Args, require_eigen_vector_t< Theta > * = nullptr>
auto	log_likelihood (F &&f, Theta &&theta, Stream *msgs, Args &&... args)
template<typename F , typename Theta , typename Stream , typename... Args, require_eigen_vector_vt< std::is_arithmetic, Theta > * = nullptr>
auto	theta_grad (F &&f, Theta &&theta, Stream *msgs, Args &&... args)
	Computes theta gradient f wrt theta and args...
template<typename F , typename Theta , typename Stream , typename... Args, require_eigen_vector_vt< std::is_arithmetic, Theta > * = nullptr>
void	ll_arg_grad (F &&f, Theta &&theta, Stream *msgs, Args &&... args)
	Computes likelihood argument gradient of f
template<typename F , typename Theta , typename Stream , typename... Args, require_eigen_vector_vt< std::is_arithmetic, Theta > * = nullptr>
auto	diagonal_hessian (F &&f, Theta &&theta, Stream *msgs, Args &&... args)
	Computes negative diagonal Hessian of f wrttheta and args...
template<typename F , typename Theta , typename Stream , typename... Args, require_eigen_vector_vt< std::is_arithmetic, Theta > * = nullptr>
auto	block_hessian (F &&f, Theta &&theta, const Eigen::Index hessian_block_size, Stream *msgs, Args &&... args)
	Computes negative block diagonal Hessian of f wrttheta and args...
template<typename F , typename Theta , typename Stream , typename... Args, require_eigen_vector_vt< std::is_arithmetic, Theta > * = nullptr>
auto	diff (F &&f, Theta &&theta, const Eigen::Index hessian_block_size, Stream *msgs, Args &&... args)
	Computes theta gradient and negative block diagonal Hessian of f wrt theta and args...
template<typename F , typename Theta , typename Stream , typename... Args, require_eigen_vector_t< Theta > * = nullptr>
Eigen::VectorXd	third_diff (F &&f, Theta &&theta, Stream &&msgs, Args &&... args)
	Compute third order derivative of f wrt theta and args...
template<typename F , typename Theta , typename AMat , typename Stream , typename... Args, require_eigen_vector_t< Theta > * = nullptr>
auto	compute_s2 (F &&f, Theta &&theta, AMat &&A, const int hessian_block_size, Stream *msgs, Args &&... args)
	The derivative of the log likelihood wrt theta evaluated at the mode.
template<typename F , typename V_t , typename Theta , typename Stream , typename... Args, require_eigen_vector_t< Theta > * = nullptr>
auto	diff_eta_implicit (F &&f, V_t &&v, Theta &&theta, Stream *msgs, Args &&... args)
	Compute second order gradient of f wrt theta and args...