Cstan::variational::advi< Model, Q, BaseRNG > | Automatic Differentiation Variational Inference |
Cstan::lang::arg_decl | |
►Cstan::services::argument | |
►Cstan::services::categorical_argument | |
Cstan::services::arg_adapt | |
►Cstan::services::arg_bfgs | |
Cstan::services::arg_lbfgs | |
Cstan::services::arg_data | |
Cstan::services::arg_diagnose | |
Cstan::services::arg_hmc | |
Cstan::services::arg_newton | |
Cstan::services::arg_nuts | |
Cstan::services::arg_optimize | |
Cstan::services::arg_output | |
Cstan::services::arg_random | |
Cstan::services::arg_rwm | |
Cstan::services::arg_sample | |
Cstan::services::arg_softabs | |
Cstan::services::arg_static | |
Cstan::services::arg_test_gradient | |
Cstan::services::arg_variational | |
Cstan::services::arg_variational_adapt | |
Cstan::services::arg_variational_fullrank | |
Cstan::services::arg_variational_meanfield | |
Cstan::services::arg_xhmc | |
►Cstan::services::unvalued_argument | |
Cstan::services::arg_dense_e | |
Cstan::services::arg_diag_e | |
Cstan::services::arg_fail | |
Cstan::services::arg_fixed_param | |
Cstan::services::arg_unit_e | |
►Cstan::services::valued_argument | |
►Cstan::services::list_argument | |
Cstan::services::arg_engine | |
Cstan::services::arg_method | |
Cstan::services::arg_metric | |
Cstan::services::arg_optimize_algo | |
Cstan::services::arg_sample_algo | |
Cstan::services::arg_test | |
Cstan::services::arg_variational_algo | |
►Cstan::services::singleton_argument< T > | |
Cstan::services::arg_adapt_delta | |
Cstan::services::arg_adapt_engaged | |
Cstan::services::arg_adapt_gamma | |
Cstan::services::arg_adapt_init_buffer | |
Cstan::services::arg_adapt_kappa | |
Cstan::services::arg_adapt_t0 | |
Cstan::services::arg_adapt_term_buffer | |
Cstan::services::arg_adapt_window | |
Cstan::services::arg_data_file | |
Cstan::services::arg_diagnostic_file | |
Cstan::services::arg_history_size | |
Cstan::services::arg_id | |
Cstan::services::arg_init | |
Cstan::services::arg_init_alpha | |
Cstan::services::arg_int_time | |
Cstan::services::arg_iter | |
Cstan::services::arg_max_depth | |
Cstan::services::arg_num_samples | |
Cstan::services::arg_num_warmup | |
Cstan::services::arg_output_file | |
Cstan::services::arg_refresh | |
Cstan::services::arg_save_iterations | |
Cstan::services::arg_save_warmup | |
Cstan::services::arg_seed | |
Cstan::services::arg_softabs_alpha | |
Cstan::services::arg_stepsize | |
Cstan::services::arg_stepsize_jitter | |
Cstan::services::arg_test_grad_eps | |
Cstan::services::arg_test_grad_err | |
Cstan::services::arg_thin | |
Cstan::services::arg_tolerance | |
Cstan::services::arg_variational_adapt_engaged | |
Cstan::services::arg_variational_adapt_iter | |
Cstan::services::arg_variational_eta | |
Cstan::services::arg_variational_eval_elbo | |
Cstan::services::arg_variational_iter | |
Cstan::services::arg_variational_num_samples | |
Cstan::services::arg_variational_output_samples | |
Cstan::services::arg_x_delta | |
Cstan::services::argument_parser | |
Cstan::services::argument_probe | |
Cstan::lang::array_literal | |
Cstan::lang::assgn | |
Cstan::lang::assignment | |
►Cstan::mcmc::base_adaptation | |
Cstan::mcmc::stepsize_adaptation | |
►Cstan::mcmc::windowed_adaptation | |
Cstan::mcmc::covar_adaptation | |
Cstan::mcmc::var_adaptation | |
►Cstan::mcmc::base_adapter | |
►Cstan::mcmc::stepsize_adapter | |
Cstan::mcmc::adapt_softabs_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Riemannian disintegration and SoftAbs metric and adaptive step size |
Cstan::mcmc::adapt_softabs_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Riemannian disintegration and SoftAbs metric and adaptive step size |
Cstan::mcmc::adapt_softabs_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Riemannian disintegration and SoftAbs metric and adaptive step size |
Cstan::mcmc::adapt_softabs_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Riemannian disintegration and SoftAbs metric and adaptive step size |
Cstan::mcmc::adapt_unit_e_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and unit metric and adaptive step size |
Cstan::mcmc::adapt_unit_e_nuts_classic< Model, BaseRNG > | |
Cstan::mcmc::adapt_unit_e_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Euclidean disintegration and unit metric and adaptive step size |
Cstan::mcmc::adapt_unit_e_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Euclidean disintegration and unit metric and adaptive step size |
Cstan::mcmc::adapt_unit_e_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Euclidean disintegration and unit metric and adaptive step size |
►Cstan::mcmc::stepsize_covar_adapter | |
Cstan::mcmc::adapt_dense_e_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and adaptive dense metric and adaptive step size |
Cstan::mcmc::adapt_dense_e_nuts_classic< Model, BaseRNG > | |
Cstan::mcmc::adapt_dense_e_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Euclidean disintegration and adative dense metric and adaptive step size |
Cstan::mcmc::adapt_dense_e_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Euclidean disintegration and adaptive dense metric and adaptive step size |
Cstan::mcmc::adapt_dense_e_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Euclidean disintegration and adaptive dense metric and adaptive step size |
►Cstan::mcmc::stepsize_var_adapter | |
Cstan::mcmc::adapt_diag_e_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and adaptive diagonal metric and adaptive step size |
Cstan::mcmc::adapt_diag_e_nuts_classic< Model, BaseRNG > | |
Cstan::mcmc::adapt_diag_e_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Euclidean disintegration and adaptive diagonal metric and adaptive step size |
Cstan::mcmc::adapt_diag_e_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Euclidean disintegration and adaptive diagonal metric and adaptive step size |
Cstan::mcmc::adapt_diag_e_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Euclidean disintegration and adaptive diagonal metric and adaptive step size |
►Cstan::variational::base_family | |
Cstan::variational::normal_fullrank | Variational family approximation with full-rank multivariate normal distribution |
Cstan::variational::normal_meanfield | Variational family approximation with mean-field (diagonal covariance) multivariate normal distribution |
Cstan::mcmc::base_hamiltonian< Model, Point, BaseRNG > | |
►Cstan::mcmc::base_hamiltonian< Model, dense_e_point, BaseRNG > | |
Cstan::mcmc::dense_e_metric< Model, BaseRNG > | |
►Cstan::mcmc::base_hamiltonian< Model, diag_e_point, BaseRNG > | |
Cstan::mcmc::diag_e_metric< Model, BaseRNG > | |
►Cstan::mcmc::base_hamiltonian< Model, softabs_point, BaseRNG > | |
Cstan::mcmc::softabs_metric< Model, BaseRNG > | |
►Cstan::mcmc::base_hamiltonian< Model, unit_e_point, BaseRNG > | |
Cstan::mcmc::unit_e_metric< Model, BaseRNG > | |
►Cstan::mcmc::base_integrator< Hamiltonian > | |
►Cstan::mcmc::base_leapfrog< Hamiltonian > | |
Cstan::mcmc::expl_leapfrog< Hamiltonian > | |
Cstan::mcmc::impl_leapfrog< Hamiltonian > | |
►Cstan::mcmc::base_integrator< dense_e_metric< Model, BaseRNG > > | |
►Cstan::mcmc::base_leapfrog< dense_e_metric< Model, BaseRNG > > | |
Cstan::mcmc::expl_leapfrog< dense_e_metric< Model, BaseRNG > > | |
►Cstan::mcmc::base_integrator< diag_e_metric< Model, BaseRNG > > | |
►Cstan::mcmc::base_leapfrog< diag_e_metric< Model, BaseRNG > > | |
Cstan::mcmc::expl_leapfrog< diag_e_metric< Model, BaseRNG > > | |
►Cstan::mcmc::base_integrator< softabs_metric< Model, BaseRNG > > | |
►Cstan::mcmc::base_leapfrog< softabs_metric< Model, BaseRNG > > | |
Cstan::mcmc::impl_leapfrog< softabs_metric< Model, BaseRNG > > | |
►Cstan::mcmc::base_integrator< unit_e_metric< Model, BaseRNG > > | |
►Cstan::mcmc::base_leapfrog< unit_e_metric< Model, BaseRNG > > | |
Cstan::mcmc::expl_leapfrog< unit_e_metric< Model, BaseRNG > > | |
►Cstan::interface_callbacks::interrupt::base_interrupt | |
Cstan::interface_callbacks::interrupt::noop | |
►Cstan::mcmc::base_mcmc | |
►Cstan::mcmc::base_hmc< Model, dense_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::base_nuts< Model, dense_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::dense_e_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and dense metric |
Cstan::mcmc::adapt_dense_e_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and adaptive dense metric and adaptive step size |
►Cstan::mcmc::base_nuts_classic< Model, dense_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::dense_e_nuts_classic< Model, BaseRNG > | |
Cstan::mcmc::adapt_dense_e_nuts_classic< Model, BaseRNG > | |
►Cstan::mcmc::base_static_hmc< Model, dense_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::dense_e_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Euclidean disintegration and dense metric |
Cstan::mcmc::adapt_dense_e_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Euclidean disintegration and adative dense metric and adaptive step size |
►Cstan::mcmc::base_static_uniform< Model, dense_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::dense_e_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Euclidean disintegration and dense metric |
Cstan::mcmc::adapt_dense_e_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Euclidean disintegration and adaptive dense metric and adaptive step size |
►Cstan::mcmc::base_xhmc< Model, dense_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::dense_e_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Euclidean disintegration and dense metric |
Cstan::mcmc::adapt_dense_e_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Euclidean disintegration and adaptive dense metric and adaptive step size |
►Cstan::mcmc::base_hmc< Model, diag_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::base_nuts< Model, diag_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::diag_e_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and diagonal metric |
Cstan::mcmc::adapt_diag_e_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and adaptive diagonal metric and adaptive step size |
►Cstan::mcmc::base_nuts_classic< Model, diag_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::diag_e_nuts_classic< Model, BaseRNG > | |
Cstan::mcmc::adapt_diag_e_nuts_classic< Model, BaseRNG > | |
►Cstan::mcmc::base_static_hmc< Model, diag_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::diag_e_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Euclidean disintegration and diagonal metric |
Cstan::mcmc::adapt_diag_e_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Euclidean disintegration and adaptive diagonal metric and adaptive step size |
►Cstan::mcmc::base_static_uniform< Model, diag_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::diag_e_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Euclidean disintegration and diagonal metric |
Cstan::mcmc::adapt_diag_e_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Euclidean disintegration and adaptive diagonal metric and adaptive step size |
►Cstan::mcmc::base_xhmc< Model, diag_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::diag_e_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Euclidean disintegration and diagonal metric |
Cstan::mcmc::adapt_diag_e_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Euclidean disintegration and adaptive diagonal metric and adaptive step size |
►Cstan::mcmc::base_hmc< Model, softabs_metric, impl_leapfrog, BaseRNG > | |
►Cstan::mcmc::base_nuts< Model, softabs_metric, impl_leapfrog, BaseRNG > | |
►Cstan::mcmc::softabs_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Riemannian disintegration and SoftAbs metric |
Cstan::mcmc::adapt_softabs_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Riemannian disintegration and SoftAbs metric and adaptive step size |
►Cstan::mcmc::base_static_hmc< Model, softabs_metric, impl_leapfrog, BaseRNG > | |
►Cstan::mcmc::softabs_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Riemannian disintegration and SoftAbs metric |
Cstan::mcmc::adapt_softabs_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Riemannian disintegration and SoftAbs metric and adaptive step size |
►Cstan::mcmc::base_static_uniform< Model, softabs_metric, impl_leapfrog, BaseRNG > | |
►Cstan::mcmc::softabs_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Riemannian disintegration and SoftAbs metric |
Cstan::mcmc::adapt_softabs_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Riemannian disintegration and SoftAbs metric and adaptive step size |
►Cstan::mcmc::base_xhmc< Model, softabs_metric, impl_leapfrog, BaseRNG > | |
►Cstan::mcmc::softabs_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Riemannian disintegration and SoftAbs metric |
Cstan::mcmc::adapt_softabs_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Riemannian disintegration and SoftAbs metric and adaptive step size |
►Cstan::mcmc::base_hmc< Model, unit_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::base_nuts< Model, unit_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::unit_e_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and unit metric |
Cstan::mcmc::adapt_unit_e_nuts< Model, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling with a Gaussian-Euclidean disintegration and unit metric and adaptive step size |
►Cstan::mcmc::base_nuts_classic< Model, unit_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::unit_e_nuts_classic< Model, BaseRNG > | |
Cstan::mcmc::adapt_unit_e_nuts_classic< Model, BaseRNG > | |
►Cstan::mcmc::base_static_hmc< Model, unit_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::unit_e_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Euclidean disintegration and unit metric |
Cstan::mcmc::adapt_unit_e_static_hmc< Model, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time with a Gaussian-Euclidean disintegration and unit metric and adaptive step size |
►Cstan::mcmc::base_static_uniform< Model, unit_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::unit_e_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Euclidean disintegration and unit metric |
Cstan::mcmc::adapt_unit_e_static_uniform< Model, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time with a Gaussian-Euclidean disintegration and unit metric and adaptive step size |
►Cstan::mcmc::base_xhmc< Model, unit_e_metric, expl_leapfrog, BaseRNG > | |
►Cstan::mcmc::unit_e_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Euclidean disintegration and unit metric |
Cstan::mcmc::adapt_unit_e_xhmc< Model, BaseRNG > | Exhausive Hamiltonian Monte Carlo (XHMC) with multinomial sampling with a Gaussian-Euclidean disintegration and unit metric and adaptive step size |
►Cstan::mcmc::base_hmc< Model, Hamiltonian, Integrator, BaseRNG > | |
Cstan::mcmc::base_nuts< Model, Hamiltonian, Integrator, BaseRNG > | The No-U-Turn sampler (NUTS) with multinomial sampling |
Cstan::mcmc::base_nuts_classic< Model, Hamiltonian, Integrator, BaseRNG > | |
Cstan::mcmc::base_static_hmc< Model, Hamiltonian, Integrator, BaseRNG > | Hamiltonian Monte Carlo implementation using the endpoint of trajectories with a static integration time |
Cstan::mcmc::base_static_uniform< Model, Hamiltonian, Integrator, BaseRNG > | Hamiltonian Monte Carlo implementation that uniformly samples from trajectories with a static integration time |
Cstan::mcmc::base_xhmc< Model, Hamiltonian, Integrator, BaseRNG > | Exhaustive Hamiltonian Monte Carlo (XHMC) with multinomial sampling |
Cstan::mcmc::fixed_param_sampler | |
►Cstan::lang::base_var_decl | |
Cstan::lang::cholesky_corr_var_decl | |
Cstan::lang::cholesky_factor_var_decl | |
Cstan::lang::corr_matrix_var_decl | |
Cstan::lang::cov_matrix_var_decl | |
Cstan::lang::double_var_decl | |
Cstan::lang::int_var_decl | |
Cstan::lang::matrix_var_decl | |
Cstan::lang::ordered_var_decl | |
Cstan::lang::positive_ordered_var_decl | |
Cstan::lang::row_vector_var_decl | |
Cstan::lang::simplex_var_decl | |
Cstan::lang::unit_vector_var_decl | |
Cstan::lang::vector_var_decl | |
►Cstan::interface_callbacks::writer::base_writer | Base_writer is an abstract base class defining the interface for Stan writer callbacks |
Cstan::interface_callbacks::writer::noop_writer | No op writer |
Cstan::interface_callbacks::writer::stream_writer | Stream_writer writes to an std::ostream |
Cstan::optimization::BFGSMinimizer< FunctorType, QNUpdateType, Scalar, DimAtCompile > | |
►Cstan::optimization::BFGSMinimizer< ModelAdaptor< M >, QNUpdateType, Scalar, DimAtCompile > | |
Cstan::optimization::BFGSLineSearch< M, QNUpdateType, Scalar, DimAtCompile > | |
Cstan::optimization::BFGSUpdate_HInv< Scalar, DimAtCompile > | |
Cstan::lang::binary_op | |
Cstan::mcmc::chains< RNG > | An mcmc::chains object stores parameter names and dimensionalities along with samples from multiple chains |
Cstan::io::cmd_line | Parses and stores command-line arguments |
Cstan::lang::conditional_op | |
Cstan::lang::conditional_statement | |
Cstan::model::cons_index_list< H, T > | Template structure for an index list consisting of a head and tail index |
Cstan::optimization::ConvergenceOptions< Scalar > | |
Cstan::lang::distribution | |
Cstan::lang::double_literal | |
Cstan::io::dump_reader | Reads data from S-plus dump format |
►CE | |
Cstan::lang::located_exception< E > | Structure for a located exception for standard library exception types that have no what-based constructors |
Cstan::services::error_codes | |
Cstan::lang::expr_type | |
Cstan::lang::expression | |
Cstan::lang::for_statement | |
Cstan::lang::fun | |
Cstan::lang::function_decl_def | |
Cstan::lang::function_decl_defs | |
Cstan::lang::function_signatures | |
►Cgrammar | |
Cstan::lang::bare_type_grammar< Iterator > | |
Cstan::lang::expression07_grammar< Iterator > | |
Cstan::lang::expression_grammar< Iterator > | |
Cstan::lang::functions_grammar< Iterator > | |
Cstan::lang::indexes_grammar< Iterator > | |
Cstan::lang::program_grammar< Iterator > | |
Cstan::lang::statement_2_grammar< Iterator > | |
Cstan::lang::statement_grammar< Iterator > | |
Cstan::lang::term_grammar< Iterator > | |
Cstan::lang::var_decls_grammar< Iterator > | |
Cstan::lang::whitespace_grammar< Iterator > | |
Cstan::lang::idx | |
Cstan::lang::increment_log_prob_statement | |
Cstan::model::index_max | Structure for an indexing from the start of a container to a specified maximum index (inclusive) |
Cstan::model::index_min | Structure for an indexing from a minimum index (inclusive) to the end of a container |
Cstan::model::index_min_max | Structure for an indexing from a minimum index (inclusive) to a maximum index (inclusive) |
Cstan::model::index_multi | Structure for an indexing consisting of multiple indexes |
Cstan::model::index_omni | Structure for an indexing that consists of all indexes for a container |
Cstan::lang::index_op | |
Cstan::lang::index_op_sliced | |
Cstan::model::index_uni | Structure for an indexing consisting of a single index |
Cstan::lang::int_literal | |
Cstan::lang::integrate_ode | |
Cstan::lang::integrate_ode_control | |
►Cstan::json::json_handler | Abstract base class for JSON handlers |
Cstan::json::json_data_handler | A json_data_handler is an implementation of a json_handler that restricts the allowed JSON text a set of Stan variable declarations in JSON format |
Cstan::lang::lb_idx | |
Cstan::optimization::LBFGSUpdate< Scalar, DimAtCompile > | Implement a limited memory version of the BFGS update |
►Clogic_error | |
Cstan::json::json_error | Exception type for JSON errors |
Cstan::optimization::LSOptions< Scalar > | |
Cstan::lang::lub_idx | |
Cstan::services::sample::mcmc_writer< Model, SampleWriter, DiagnosticWriter, MessageWriter > | Mcmc_writer writes out headers and samples |
Cstan::model::model_functional< M > | |
Cstan::optimization::ModelAdaptor< M > | |
Cstan::lang::multi_idx | |
Cstan::lang::nil | Placeholder struct for boost::variant default ctors |
Cstan::model::nil_index_list | Structure for an empty (size zero) index list |
Cstan::lang::no_op_statement | |
Cstan::mcmc::nuts_util | |
Cstan::lang::omni_idx | |
►Cstan::lang::phoenix_functor_binary | This is the base class for binary functors that are adapted to lazy semantic actions by boost::phoenix |
Cstan::lang::add_conditional_body | |
Cstan::lang::add_while_body | |
Cstan::lang::assign_lhs | |
Cstan::lang::empty_range | |
Cstan::lang::is_prob_fun | |
Cstan::lang::remove_loop_identifier | |
Cstan::lang::unscope_locals | |
Cstan::lang::unscope_variables | |
Cstan::lang::validate_int_expression | |
►Cstan::lang::phoenix_functor_quaternary | This is the base class for quatenary functors that are adapted to lazy semantic actions by boost::phoenix |
Cstan::lang::add_conditional_condition | |
Cstan::lang::add_expression_dimss | |
Cstan::lang::add_fun_var | |
Cstan::lang::add_idxs | |
Cstan::lang::add_while_condition | |
Cstan::lang::left_division_expr | |
Cstan::lang::modulus_expr | |
Cstan::lang::negate_expr | |
Cstan::lang::set_double_range_lower | |
Cstan::lang::set_double_range_upper | |
Cstan::lang::set_int_range_lower | |
Cstan::lang::set_int_range_upper | |
Cstan::lang::set_void_function | |
Cstan::lang::validate_declarations | |
Cstan::lang::validate_integrate_ode | |
Cstan::lang::validate_integrate_ode_control | |
Cstan::lang::validate_sample | |
►Cstan::lang::phoenix_functor_quinary | This is the base class for quinary functors that are adapted to lazy semantic actions by boost::phoenix |
Cstan::lang::add_function_signature | |
Cstan::lang::add_loop_identifier | |
Cstan::lang::binary_op_expr | |
Cstan::lang::exponentiation_expr | |
Cstan::lang::program_error | |
Cstan::lang::set_fun_type_named | |
Cstan::lang::set_var_type | |
Cstan::lang::validate_assignment | |
Cstan::lang::validate_decl_constraints | |
Cstan::lang::validate_int_data_expr | |
►Cstan::lang::phoenix_functor_senary | This is the base class for senary functors that are adapted to lazy semantic actions by boost::phoenix |
Cstan::lang::add_var | |
Cstan::lang::identifier_to_var | |
Cstan::lang::phoenix_functor_septenary | This is the base class for septenary functors that are adapted to lazy semantic actions by boost::phoenix |
►Cstan::lang::phoenix_functor_ternary | This is the base class for ternary functors that are adapted to lazy semantic actions by boost::phoenix |
Cstan::lang::add_line_number | |
Cstan::lang::addition_expr3 | |
Cstan::lang::division_expr | |
Cstan::lang::elt_division_expr | |
Cstan::lang::elt_multiplication_expr | |
Cstan::lang::expression_as_statement | |
Cstan::lang::logical_negate_expr | |
Cstan::lang::multiplication_expr | |
Cstan::lang::set_allows_sampling_origin | |
Cstan::lang::subtraction_expr3 | |
Cstan::lang::transpose_expr | |
Cstan::lang::validate_allow_sample | |
Cstan::lang::validate_assgn | |
Cstan::lang::validate_conditional_op | |
Cstan::lang::validate_expr_type3 | |
Cstan::lang::validate_identifier | |
Cstan::lang::validate_int_expr | |
Cstan::lang::validate_int_expr_warn | |
Cstan::lang::validate_ints_expression | |
Cstan::lang::validate_non_void_arg_function | |
Cstan::lang::validate_non_void_expression | |
Cstan::lang::validate_pmf_pdf_variate | |
Cstan::lang::validate_prob_fun | |
Cstan::lang::validate_return_allowed | |
Cstan::lang::validate_return_type | |
Cstan::lang::validate_void_return_allowed | |
►Cstan::lang::phoenix_functor_unary | This is the base class for unnary functors that are adapted to lazy semantic actions by boost::phoenix |
Cstan::lang::add_lp_var | |
Cstan::lang::copy_square_cholesky_dimension_if_necessary | |
Cstan::lang::deprecate_increment_log_prob | |
Cstan::lang::deprecate_old_assignment_op | |
Cstan::lang::deprecated_integrate_ode | |
Cstan::lang::increment_size_t | |
Cstan::lang::remove_lp_var | |
Cstan::lang::scope_lp | |
Cstan::lang::set_no_op | |
Cstan::lang::set_omni_idx | |
Cstan::lang::set_void_return | |
Cstan::lang::print_statement | |
Cstan::lang::printable | |
Cstan::model::prob_grad | The prob_grad class represents the basic parameter holders for a model |
Cstan::lang::program | |
►Cstan::mcmc::ps_point | Point in a generic phase space |
Cstan::mcmc::dense_e_point | Point in a phase space with a base Euclidean manifold with dense metric |
Cstan::mcmc::diag_e_point | Point in a phase space with a base Euclidean manifold with diagonal metric |
Cstan::mcmc::softabs_point | Point in a phase space with a base Riemannian manifold with SoftAbs metric |
Cstan::mcmc::unit_e_point | Point in a phase space with a base Euclidean manifold with unit metric |
Cstan::lang::range | |
Cstan::io::reader< T > | A stream-based reader for integer, scalar, vector, matrix and array data types, with Jacobian calculations |
Cstan::lang::reject_statement | |
Cstan::lang::phoenix_functor_unary::result< class > | Declare result to be a template struct |
Cstan::lang::phoenix_functor_quaternary::result< class > | Declare result to be a template struct |
Cstan::lang::phoenix_functor_quinary::result< class > | Declare result to be a template struct |
Cstan::lang::phoenix_functor_senary::result< class > | Declare result to be a template struct |
Cstan::lang::phoenix_functor_septenary::result< class > | Declare result to be a template struct |
Cstan::lang::phoenix_functor_binary::result< class > | Declare result to be a template struct |
Cstan::lang::phoenix_functor_ternary::result< class > | Declare result to be a template struct |
Cstan::lang::phoenix_functor_unary::result< F(T1)> | Specialize as required by Phoenix to functional form with typedef of return type |
Cstan::lang::phoenix_functor_binary::result< F(T1, T2)> | Specialize as required by Phoenix to functional form with typedef of return type |
Cstan::lang::phoenix_functor_ternary::result< F(T1, T2, T3)> | Specialize as required by Phoenix to functional form with typedef of return type |
Cstan::lang::phoenix_functor_quaternary::result< F(T1, T2, T3, T4)> | Specialize as required by Phoenix to functional form with typedef of return type |
Cstan::lang::phoenix_functor_quinary::result< F(T1, T2, T3, T4, T5)> | Specialize as required by Phoenix to functional form with typedef of return type |
Cstan::lang::phoenix_functor_senary::result< F(T1, T2, T3, T4, T5, T6)> | Specialize as required by Phoenix to functional form with typedef of return type |
Cstan::lang::phoenix_functor_septenary::result< F(T1, T2, T3, T4, T5, T6, T7)> | Specialize as required by Phoenix to functional form with typedef of return type |
Cstan::lang::return_statement | |
Cstan::model::rvalue_return< C, L > | Primary template class for metaprogram to calculate return value for model::rvalue() for the container or scalar type and index list type specified in the template parameters |
Cstan::model::rvalue_return< C, nil_index_list > | Template class specialization for nil indexes, which provide the container type as the return type |
Cstan::model::rvalue_return< Eigen::Matrix< T, 1, Eigen::Dynamic >, cons_index_list< index_uni, nil_index_list > > | Template class specialization for an Eigen row vector and one single index |
Cstan::model::rvalue_return< Eigen::Matrix< T, Eigen::Dynamic, 1 >, cons_index_list< index_uni, nil_index_list > > | Template class specialization for an Eigen vector and one single index |
Cstan::model::rvalue_return< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic >, cons_index_list< I, cons_index_list< index_uni, nil_index_list > > > | Template specialization for an Eigen matrix with one multiple index followed by one single index |
Cstan::model::rvalue_return< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic >, cons_index_list< I1, cons_index_list< I2, nil_index_list > > > | Template specialization for an Eigen matrix and two multiple indexes |
Cstan::model::rvalue_return< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic >, cons_index_list< index_uni, cons_index_list< I, nil_index_list > > > | Template specialization for an Eigen matrix with one single index followed by one multiple index |
Cstan::model::rvalue_return< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic >, cons_index_list< index_uni, cons_index_list< index_uni, nil_index_list > > > | Template specialization for an Eigen matrix with two single indexes |
Cstan::model::rvalue_return< Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic >, cons_index_list< index_uni, nil_index_list > > | Template class specialization for an Eigen matrix and one single index |
Cstan::model::rvalue_return< Eigen::Matrix< T, R, C >, cons_index_list< I, nil_index_list > > | Template class specialization for an Eigen matrix, vector or rwo vector and one multiple index |
Cstan::model::rvalue_return< std::vector< C >, cons_index_list< I, L > > | Template specialization for a standard vector whose index list starts with a multiple index |
Cstan::model::rvalue_return< std::vector< C >, cons_index_list< index_uni, L > > | Template specialization for a standard vector whose index list starts with a single index |
Cstan::lang::sample | |
Cstan::mcmc::sample | |
Cstan::mcmc::softabs_fun< Model > | |
Cstan::io::stan_csv | |
Cstan::io::stan_csv_adaptation | |
Cstan::io::stan_csv_metadata | |
Cstan::io::stan_csv_reader | Reads from a Stan output csv file |
Cstan::io::stan_csv_timing | |
Cstan::lang::statement | |
Cstan::lang::statements | |
►Cstatic_visitor | |
Cstan::lang::contains_nonparam_var | |
Cstan::lang::contains_var | |
Cstan::lang::data_only_expression | |
Cstan::lang::expression_type_vis | |
Cstan::lang::is_multi_index_vis | |
Cstan::lang::is_nil_op | |
Cstan::lang::is_no_op_statement_vis | |
Cstan::lang::is_numbered_statement_vis | |
Cstan::lang::name_vis | |
Cstan::lang::returns_type_vis | |
Cstan::lang::validate_no_constraints_vis | |
Cstan::lang::var_decl_base_type_vis | |
Cstan::lang::var_occurs_vis | |
Cstan::services::type_name< T > | |
Cstan::services::type_name< bool > | |
Cstan::services::type_name< double > | |
Cstan::services::type_name< int > | |
Cstan::services::type_name< std::string > | |
Cstan::services::type_name< unsigned int > | |
Cstan::lang::ub_idx | |
Cstan::lang::unary_op | |
Cstan::lang::uni_idx | |
►Cstan::io::var_context | A var_reader reads array variables of integer and floating point type by name and dimension |
Cstan::io::array_var_context | An array_var_context object represents a named arrays with dimensions constructed from an array, a vector of names, and a vector of all dimensions for each element |
Cstan::io::chained_var_context | A chained_var_context object represents two objects of var_context as one |
Cstan::io::dump | Represents named arrays with dimensions |
Cstan::json::json_data | A json_data is a var_context object that represents a set of named values which are typed to either double or int and can be either scalar value or a non-empty array of values of any dimensionality |
Cstan::interface_callbacks::var_context_factory::var_context_factory< VARCON > | |
►Cstan::interface_callbacks::var_context_factory::var_context_factory< stan::io::dump > | |
Cstan::interface_callbacks::var_context_factory::dump_factory | |
Cstan::lang::var_decl | |
Cstan::lang::variable | |
Cstan::lang::variable_dims | |
Cstan::lang::variable_map | |
►Cstan::lang::visgen | Generic visitor with output for extension |
Cstan::lang::constrained_param_names_visgen | |
Cstan::lang::dump_member_var_visgen | |
Cstan::lang::expression_visgen | |
Cstan::lang::generate_init_vars_visgen | |
Cstan::lang::generate_init_visgen | |
Cstan::lang::generate_local_var_init_nan_visgen | |
Cstan::lang::idx_user_visgen | |
Cstan::lang::idx_visgen | |
Cstan::lang::init_local_var_visgen | |
Cstan::lang::local_var_decl_visgen | |
Cstan::lang::member_var_decl_visgen | |
Cstan::lang::printable_visgen | |
Cstan::lang::set_param_ranges_visgen | |
Cstan::lang::statement_visgen | |
Cstan::lang::unconstrained_param_names_visgen | |
Cstan::lang::validate_transformed_params_visgen | |
Cstan::lang::validate_var_decl_visgen | |
Cstan::lang::var_resizing_visgen | |
Cstan::lang::var_size_validating_visgen | |
Cstan::lang::write_array_vars_visgen | |
Cstan::lang::write_array_visgen | |
Cstan::lang::write_dims_visgen | |
Cstan::lang::write_param_names_visgen | |
Cstan::lang::while_statement | |
Cstan::io::writer< T > | A stream-based writer for integer, scalar, vector, matrix and array data types, which transforms from constrained to a sequence of constrained variables |