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Stan
2.10.0
probability, sampling & optimization
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The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and unit metric and adaptive step size. More...
#include <adapt_unit_e_nuts.hpp>
Public Member Functions | |
adapt_unit_e_nuts (const Model &model, BaseRNG &rng) | |
~adapt_unit_e_nuts () | |
sample | transition (sample &init_sample, interface_callbacks::writer::base_writer &info_writer, interface_callbacks::writer::base_writer &error_writer) |
void | disengage_adaptation () |
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unit_e_nuts (const Model &model, BaseRNG &rng) | |
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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... | |
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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) |
unit_e_metric< 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 () |
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base_mcmc () | |
virtual | ~base_mcmc () |
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stepsize_adapter () | |
stepsize_adaptation & | get_stepsize_adaptation () |
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base_adapter () | |
virtual void | engage_adaptation () |
bool | adapting () |
Additional Inherited Members | |
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int | depth_ |
int | max_depth_ |
double | max_deltaH_ |
int | n_leapfrog_ |
int | divergent_ |
double | energy_ |
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unit_e_metric< Model, BaseRNG >::PointType | z_ |
expl_leapfrog< unit_e_metric< Model, BaseRNG > > | integrator_ |
unit_e_metric< Model, BaseRNG > | hamiltonian_ |
BaseRNG & | rand_int_ |
boost::uniform_01< BaseRNG & > | rand_uniform_ |
double | nom_epsilon_ |
double | epsilon_ |
double | epsilon_jitter_ |
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stepsize_adaptation | stepsize_adaptation_ |
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bool | adapt_flag_ |
The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and unit metric and adaptive step size.
Definition at line 16 of file adapt_unit_e_nuts.hpp.
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inline |
Definition at line 19 of file adapt_unit_e_nuts.hpp.
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inline |
Definition at line 22 of file adapt_unit_e_nuts.hpp.
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inlinevirtual |
Reimplemented from stan::mcmc::base_adapter.
Definition at line 39 of file adapt_unit_e_nuts.hpp.
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inlinevirtual |
Implements stan::mcmc::base_mcmc.
Definition at line 25 of file adapt_unit_e_nuts.hpp.