stan::mcmc Namespace Reference

Markov chain Monte Carlo samplers. More...

Classes
class	adaptive_cdhmc
	Adaptive "constant distance" Hamiltonian Monte Carlo (CDHMC) sampler. More...
class	adaptive_hmc
	Adaptive Hamiltonian Monte Carlo (HMC) sampler. More...
class	adaptive_sampler
	An abstract base class for adaptive samplers. More...
class	chains
	An mcmc::chains object stores parameter names and dimensionalities along with samples from multiple chains. More...
class	DualAverage
	Implements Nesterov's dual average algorithm. More...
class	hmc_base
class	nuts
	No-U-Turn Sampler (NUTS). More...
class	nuts_diag
	No-U-Turn Sampler (NUTS) with varying step sizes. More...
class	nuts_massgiven
	No-U-Turn Sampler (NUTS) with varying step sizes. More...
class	nuts_nondiag
	No-U-Turn Sampler (NUTS) with varying step sizes. More...
class	sample
	Representation of a MCMC sample. More...

Functions
void	write_error_msgs (std::ostream *error_msgs, const std::domain_error &e)
double	leapfrog (stan::model::prob_grad &model, std::vector< int > z, std::vector< double > &x, std::vector< double > &m, std::vector< double > &g, double epsilon, std::ostream *error_msgs=0, std::ostream *output_msgs=0)
	Computes the log probability for a single leapfrog step in Hamiltonian Monte Carlo.
double	rescaled_leapfrog (stan::model::prob_grad &model, std::vector< int > z, const std::vector< double > &step_sizes, std::vector< double > &x, std::vector< double > &m, std::vector< double > &g, double epsilon, std::ostream *error_msgs=0, std::ostream *output_msgs=0)
double	nondiag_leapfrog (stan::model::prob_grad &model, std::vector< int > z, const Eigen::MatrixXd &_cov_L, std::vector< double > &x, std::vector< double > &m, std::vector< double > &g, double epsilon, std::ostream *error_msgs=0, std::ostream *output_msgs=0)
void	read_cov (std::string &cov_file, Eigen::MatrixXd &cov_L)
int	sample_unnorm_log (std::vector< double > probs, boost::uniform_01< boost::mt19937 & > &rand_uniform_01)

Detailed Description

Markov chain Monte Carlo samplers.

Function Documentation

double stan::mcmc::leapfrog	(	stan::model::prob_grad &	model,
		std::vector< int >	z,
		std::vector< double > &	x,
		std::vector< double > &	m,
		std::vector< double > &	g,
		double	epsilon,
		std::ostream *	error_msgs = 0,
		std::ostream *	output_msgs = 0
	)

Computes the log probability for a single leapfrog step in Hamiltonian Monte Carlo.

If a domain error occurs when calling the model's grad_log_prob(), this function returns -inf. Domain errors can occur when distribution functions are called with parameters out of support.

Parameters

[in]	model	Probability model with gradients.
[in]	z	Integer parameters.
[in]	x	Real parameters
[in,out]	m	Momentum.
[in,out]	g	Gradient at x, z.
[in]	epsilon	Step size used in Hamiltonian dynamics.
[in,out]	error_msgs	Output stream for error messages.
[in,out]	output_msgs	Output stream for output messages.

Returns

the log probability of x and m.

Definition at line 58 of file util.hpp.

double stan::mcmc::nondiag_leapfrog	(	stan::model::prob_grad &	model,
		std::vector< int >	z,
		const Eigen::MatrixXd &	_cov_L,
		std::vector< double > &	x,
		std::vector< double > &	m,
		std::vector< double > &	g,
		double	epsilon,
		std::ostream *	error_msgs = 0,
		std::ostream *	output_msgs = 0
	)

Definition at line 104 of file util.hpp.

void stan::mcmc::read_cov	(	std::string &	cov_file,
		Eigen::MatrixXd &	cov_L
	)

Definition at line 128 of file util.hpp.

double stan::mcmc::rescaled_leapfrog	(	stan::model::prob_grad &	model,
		std::vector< int >	z,
		const std::vector< double > &	step_sizes,
		std::vector< double > &	x,
		std::vector< double > &	m,
		std::vector< double > &	g,
		double	epsilon,
		std::ostream *	error_msgs = 0,
		std::ostream *	output_msgs = 0
	)

Definition at line 80 of file util.hpp.

int stan::mcmc::sample_unnorm_log	(	std::vector< double >	probs,
		boost::uniform_01< boost::mt19937 & > &	rand_uniform_01
	)

Definition at line 147 of file util.hpp.

void stan::mcmc::write_error_msgs	(	std::ostream *	error_msgs,
		const std::domain_error &	e
	)

Definition at line 20 of file util.hpp.