Public Types
typedef Eigen::Matrix< Scalar, DimAtCompile, 1 >	VectorT

typedef Eigen::Matrix< Scalar, DimAtCompile, DimAtCompile >	HessianT

Public Member Functions
Scalar	update (const VectorT &yk, const VectorT &sk, bool reset=false)
	Update the inverse Hessian approximation. More...

void	search_direction (VectorT &pk, const VectorT &gk) const
	Compute the search direction based on the current (inverse) Hessian approximation and given gradient. More...

Detailed Description

Definition at line 10 of file bfgs_update.hpp.

Member Typedef Documentation

template<typename Scalar = double, int DimAtCompile = Eigen::Dynamic>

typedef Eigen::Matrix<Scalar,DimAtCompile,DimAtCompile> stan::optimization::BFGSUpdate_HInv< Scalar, DimAtCompile >::HessianT

Definition at line 13 of file bfgs_update.hpp.

template<typename Scalar = double, int DimAtCompile = Eigen::Dynamic>

typedef Eigen::Matrix<Scalar,DimAtCompile,1> stan::optimization::BFGSUpdate_HInv< Scalar, DimAtCompile >::VectorT

Definition at line 12 of file bfgs_update.hpp.

template<typename Scalar = double, int DimAtCompile = Eigen::Dynamic>

void stan::optimization::BFGSUpdate_HInv< Scalar, DimAtCompile >::search_direction	(	VectorT &	pk,
		const VectorT &	gk
	)		const

inline

Compute the search direction based on the current (inverse) Hessian approximation and given gradient.

Parameters

[out]	pk	The negative product of the inverse Hessian and gradient direction gk.
[in]	gk	Gradient direction.

Definition at line 56 of file bfgs_update.hpp.

template<typename Scalar = double, int DimAtCompile = Eigen::Dynamic>

Scalar stan::optimization::BFGSUpdate_HInv< Scalar, DimAtCompile >::update	(	const VectorT &	yk,
		const VectorT &	sk,
		bool	reset = `false`
	)

inline

Update the inverse Hessian approximation.

Parameters

yk	Difference between the current and previous gradient vector.
sk	Difference between the current and previous state vector.
reset	Whether to reset the approximation, forgetting about previous values.

Returns: In the case of a reset, returns the optimal scaling of the initial Hessian approximation which is useful for predicting step-sizes.

Definition at line 26 of file bfgs_update.hpp.

The documentation for this class was generated from the following file: