The prob_grad class represents densities with fixed numbers of discrete and scalar parameters and the gradient with respet to the scalar parameters. More...

#include <prob_grad.hpp>

Inheritance diagram for stan::model::prob_grad:

Public Member Functions
	prob_grad (size_t num_params_r)

	prob_grad (size_t num_params_r, std::vector< std::pair< int, int > > &param_ranges_i)

virtual	~prob_grad ()

void	set_num_params_r (size_t num_params_r)

void	setparam_ranges_i__ (std::vector< std::pair< int, int > > param_ranges_i)

virtual size_t	num_params_r ()

virtual size_t	num_params_i ()

std::pair< int, int >	param_range_i (size_t idx)

void	set_param_range_i_lower (size_t idx, int low)

void	set_param_range_i_upper (size_t idx, int up)

int	param_range_i_lower (size_t idx)

int	param_range_i_upper (size_t idx)

virtual void	init (std::vector< double > &params_r, std::vector< int > &params_i)

virtual double	grad_log_prob (std::vector< double > &params_r, std::vector< int > &params_i, std::vector< double > &gradient, std::ostream *output_stream=0)=0

virtual double	log_prob (std::vector< double > &params_r, std::vector< int > &params_i, std::ostream *output_stream=0)=0

virtual double	grad_hess_log_prob (std::vector< double > &params_r, std::vector< int > &params_i, std::vector< double > &gradient, std::vector< double > &hessian, std::ostream *output_stream=0)
	Evaluate the log-probability, its gradient, and its Hessian at params_r. More...

virtual double	log_prob_star (size_t idx, int val, std::vector< double > &params_r, std::vector< int > &params_i, std::ostream *output_stream=0)

virtual void	write_csv (std::vector< double > &params_r, std::vector< int > &params_i, std::ostream &o, std::ostream *output_stream=0)
	Write the parameters on a single line in CSV format. More...

void	finite_diff_grad (std::vector< double > &params_r, std::vector< int > &params_i, std::vector< double > &grad, double epsilon=1e-6, std::ostream *output_stream=0)
	Compute the gradient using finite differences for the specified parameters, writing the result into the specified gradient, using the specified perturbation. More...

int	test_gradients (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 *output_stream=0)
	Test the grad_log_prob() function's ability to produce accurate gradients using finite differences. More...

Protected Attributes
size_t	num_params_r__

std::vector< std::pair< int, int > >	param_ranges_i__

Detailed Description

The prob_grad class represents densities with fixed numbers of discrete and scalar parameters and the gradient with respet to the scalar parameters.

Definition at line 24 of file prob_grad.hpp.

Constructor & Destructor Documentation

◆ prob_grad() [1/2]

stan::model::prob_grad::prob_grad ( size_t num_params_r )

inline

Definition at line 31 of file prob_grad.hpp.

◆ prob_grad() [2/2]

stan::model::prob_grad::prob_grad	(	size_t	num_params_r,
		std::vector< std::pair< int, int > > &	param_ranges_i
	)

inline

Definition at line 36 of file prob_grad.hpp.

◆ ~prob_grad()

virtual stan::model::prob_grad::~prob_grad ( )

inlinevirtual

Definition at line 42 of file prob_grad.hpp.

Member Function Documentation

◆ finite_diff_grad()

void stan::model::prob_grad::finite_diff_grad	(	std::vector< double > &	params_r,
		std::vector< int > &	params_i,
		std::vector< double > &	grad,
		double	epsilon = `1e-6`,
		std::ostream *	output_stream = `0`
	)

inline

Compute the gradient using finite differences for the specified parameters, writing the result into the specified gradient, using the specified perturbation.

Parameters

	params_r	Real-valued parameters.
	params_i	Integer-valued parameters.
[out]	grad	Vector into which gradient is written.
	epsilon
[in,out]	output_stream

Definition at line 201 of file prob_grad.hpp.

◆ grad_hess_log_prob()

virtual double stan::model::prob_grad::grad_hess_log_prob	(	std::vector< double > &	params_r,
		std::vector< int > &	params_i,
		std::vector< double > &	gradient,
		std::vector< double > &	hessian,
		std::ostream *	output_stream = `0`
	)

inlinevirtual

Evaluate the log-probability, its gradient, and its Hessian at params_r.

This default version computes the Hessian numerically by finite-differencing the gradient, at a cost of O(params_r.size()^2).

Parameters

params_r	Real-valued parameter vector.
params_i	Integer-valued parameter vector.
gradient	Vector to write gradient to.
hessian	Vector to write gradient to. hessian[i*D + j] gives the element at the ith row and jth column of the Hessian (where D=params_r.size()).
output_stream	Stream to which print statements in Stan programs are written, default is 0

Definition at line 112 of file prob_grad.hpp.

◆ grad_log_prob()

virtual double stan::model::prob_grad::grad_log_prob	(	std::vector< double > &	params_r,
		std::vector< int > &	params_i,
		std::vector< double > &	gradient,
		std::ostream *	output_stream = `0`
	)

pure virtual

Implemented in stan::model::prob_grad_ad.

◆ init()

virtual void stan::model::prob_grad::init	(	std::vector< double > &	params_r,
		std::vector< int > &	params_i
	)

inlinevirtual

Definition at line 80 of file prob_grad.hpp.

◆ log_prob()

virtual double stan::model::prob_grad::log_prob	(	std::vector< double > &	params_r,
		std::vector< int > &	params_i,
		std::ostream *	output_stream = `0`
	)

pure virtual

Implemented in stan::model::prob_grad_ad.

◆ log_prob_star()

virtual double stan::model::prob_grad::log_prob_star	(	size_t	idx,
		int	val,
		std::vector< double > &	params_r,
		std::vector< int > &	params_i,
		std::ostream *	output_stream = `0`
	)

inlinevirtual

Definition at line 144 of file prob_grad.hpp.

◆ num_params_i()

virtual size_t stan::model::prob_grad::num_params_i ( )

inlinevirtual

Definition at line 56 of file prob_grad.hpp.

◆ num_params_r()

virtual size_t stan::model::prob_grad::num_params_r ( )

inlinevirtual

Definition at line 52 of file prob_grad.hpp.

◆ param_range_i()

std::pair<int,int> stan::model::prob_grad::param_range_i ( size_t idx )

inline

Definition at line 60 of file prob_grad.hpp.

◆ param_range_i_lower()

int stan::model::prob_grad::param_range_i_lower ( size_t idx )

inline

Definition at line 72 of file prob_grad.hpp.

◆ param_range_i_upper()

int stan::model::prob_grad::param_range_i_upper ( size_t idx )

inline

Definition at line 76 of file prob_grad.hpp.

◆ set_num_params_r()

void stan::model::prob_grad::set_num_params_r ( size_t num_params_r )

inline

Definition at line 44 of file prob_grad.hpp.

◆ set_param_range_i_lower()

void stan::model::prob_grad::set_param_range_i_lower	(	size_t	idx,
		int	low
	)

inline

Definition at line 64 of file prob_grad.hpp.

◆ set_param_range_i_upper()

void stan::model::prob_grad::set_param_range_i_upper	(	size_t	idx,
		int	up
	)

inline

Definition at line 68 of file prob_grad.hpp.

◆ setparam_ranges_i__()

void stan::model::prob_grad::setparam_ranges_i__ ( std::vector< std::pair< int, int > > param_ranges_i )

inline

Definition at line 48 of file prob_grad.hpp.

◆ test_gradients()

int stan::model::prob_grad::test_gradients	(	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 *	output_stream = `0`
	)

inline

Test the grad_log_prob() function's ability to produce accurate gradients using finite differences.

This shouldn't be necessary when using autodiff, but is useful for finding bugs in hand-written code (or agrad).

Parameters

params_r	Real-valued parameter vector.
params_i	Integer-valued parameter vector.
epsilon	Real-valued scalar saying how much to perturb
error	Real-valued scalar saying how much error to allow
o	Output stream for messages. params_r. Defaults to 1e-6.
output_stream	Stream to which Stan programs write.

Returns: number of failed gradient comparisons versus allowed error, so 0 if all gradients pass

Definition at line 236 of file prob_grad.hpp.

◆ write_csv()

virtual void stan::model::prob_grad::write_csv	(	std::vector< double > &	params_r,
		std::vector< int > &	params_i,
		std::ostream &	o,
		std::ostream *	output_stream = `0`
	)

inlinevirtual

Write the parameters on a single line in CSV format.

The implementation in this abstract base class writes out the free parameters as viwed by HMC. Subclasses may extend this class and override this implementation to return constrained values which may differ in both number and scale from the raw unconstrained parameters.

Parameters

params_r	Real-valued parameter vector.
params_i	Integer-valued parameter vector. @params o Stream to which CSV file is written
output_stream	Stream to which print statements in Stan programs are written, default is 0

Definition at line 177 of file prob_grad.hpp.

Member Data Documentation

◆ num_params_r__

size_t stan::model::prob_grad::num_params_r__

protected

Definition at line 26 of file prob_grad.hpp.

◆ param_ranges_i__

std::vector<std::pair<int,int> > stan::model::prob_grad::param_ranges_i__

protected

Definition at line 27 of file prob_grad.hpp.

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

src/stan/model/prob_grad.hpp

Public Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ prob_grad() [1/2]

◆ prob_grad() [2/2]

◆ ~prob_grad()

Member Function Documentation

◆ finite_diff_grad()

◆ grad_hess_log_prob()

◆ grad_log_prob()

◆ init()

◆ log_prob()

◆ log_prob_star()

◆ num_params_i()

◆ num_params_r()

◆ param_range_i()

◆ param_range_i_lower()

◆ param_range_i_upper()

◆ set_num_params_r()

◆ set_param_range_i_lower()

◆ set_param_range_i_upper()

◆ setparam_ranges_i__()

◆ test_gradients()

◆ write_csv()

Member Data Documentation

◆ num_params_r__

◆ param_ranges_i__