|
| base_nuts (const Model &model, BaseRNG &rng) |
|
| ~base_nuts () |
|
void | set_max_depth (int d) |
|
void | set_max_delta (double d) |
|
int | get_max_depth () |
|
double | get_max_delta () |
|
sample | transition (sample &init_sample, interface_callbacks::writer::base_writer &info_writer, interface_callbacks::writer::base_writer &error_writer) |
|
void | get_sampler_param_names (std::vector< std::string > &names) |
|
void | get_sampler_params (std::vector< double > &values) |
|
bool | compute_criterion (Eigen::VectorXd &p_sharp_minus, Eigen::VectorXd &p_sharp_plus, Eigen::VectorXd &rho) |
|
int | build_tree (int depth, Eigen::VectorXd &rho, ps_point &z_propose, double H0, double sign, int &n_leapfrog, double &log_sum_weight, double &sum_metro_prob, interface_callbacks::writer::base_writer &info_writer, interface_callbacks::writer::base_writer &error_writer) |
| Recursively build a new subtree to completion or until the subtree becomes invalid. More...
|
|
| base_hmc (const Model &model, BaseRNG &rng) |
|
void | write_sampler_state (interface_callbacks::writer::base_writer &writer) |
|
void | get_sampler_diagnostic_names (std::vector< std::string > &model_names, std::vector< std::string > &names) |
|
void | get_sampler_diagnostics (std::vector< double > &values) |
|
void | seed (const Eigen::VectorXd &q) |
|
void | init_hamiltonian (interface_callbacks::writer::base_writer &info_writer, interface_callbacks::writer::base_writer &error_writer) |
|
void | init_stepsize (interface_callbacks::writer::base_writer &info_writer, interface_callbacks::writer::base_writer &error_writer) |
|
Hamiltonian< Model, BaseRNG >::PointType & | z () |
|
virtual void | set_nominal_stepsize (double e) |
|
double | get_nominal_stepsize () |
|
double | get_current_stepsize () |
|
virtual void | set_stepsize_jitter (double j) |
|
double | get_stepsize_jitter () |
|
void | sample_stepsize () |
|
| base_mcmc () |
|
virtual | ~base_mcmc () |
|
template<class Model, template< class, class > class Hamiltonian, template< class > class Integrator, class BaseRNG>
class stan::mcmc::base_nuts< Model, Hamiltonian, Integrator, BaseRNG >
The No-U-Turn sampler (NUTS) with multinomial sampling.
Definition at line 22 of file base_nuts.hpp.
template<class Model, template< class, class > class Hamiltonian, template< class > class Integrator, class BaseRNG>
int stan::mcmc::base_nuts< Model, Hamiltonian, Integrator, BaseRNG >::build_tree |
( |
int |
depth, |
|
|
Eigen::VectorXd & |
rho, |
|
|
ps_point & |
z_propose, |
|
|
double |
H0, |
|
|
double |
sign, |
|
|
int & |
n_leapfrog, |
|
|
double & |
log_sum_weight, |
|
|
double & |
sum_metro_prob, |
|
|
interface_callbacks::writer::base_writer & |
info_writer, |
|
|
interface_callbacks::writer::base_writer & |
error_writer |
|
) |
| |
|
inline |
Recursively build a new subtree to completion or until the subtree becomes invalid.
Returns validity of the resulting subtree.
- Parameters
-
depth | Depth of the desired subtree |
rho | Summed momentum across trajectory |
z_propose | State proposed from subtree |
H0 | Hamiltonian of initial state |
sign | Direction in time to built subtree |
n_leapfrog | Summed number of leapfrog evaluations |
log_sum_weight | Log of summed weights across trajectory |
sum_metro_prob | Summed Metropolis probabilities across trajectory |
info_writer | Stream for information messages |
error_writer | Stream for error messages |
Definition at line 183 of file base_nuts.hpp.