Full Bayesian Inference for Hidden Markov Models

browse_model | Load the underlying Stan code into an IDE or browser... |

check | Verify that the object is a valid specification. TO BE... |

classify_alpha | Classify observations based on filtered probabilities. |

classify_gamma | Classify observations based on smoothed probabilities. |

classify_quantity | Classify observations based on latent state probabilities. |

classify_zstar | Assign the hidden states to the most likely path (_zstar_). |

compile | Compile a specified model. |

Density | Create a representation of a probability mass or density... |

explain | Create an user-friendly text describing the model. |

explain_initial | Create an outline of the initial distribution model. |

explain_observation | Create an outline of the observation model. |

explain_transition | Create an outline of the transition model. |

extract | Extract quantities from a model fitted with BayesHMM. |

extract_alpha | Extract the estimates of the filtered probability (alpha). |

extract_best | Return the optimization object for the run with the hightest... |

extract_data | Extract the dataset used to fit the model. |

extract_filename | Extract the path to file with the underlying Stan code... |

extract_gamma | Extract the estimates of the smoothed probability (gamma). |

extract_grid | Extract summary results from the optimization procedure. |

extract_grid.Optimization | Extract summary results from the optimization procedure. |

extract_grid.OptimizationList | Extract summary results from more than one run of the... |

extract_K | Extract the number of hidden states _K_. |

extract_n_chains | Extract the number of chains (M). |

extract_obs_parameters | Extract the estimates of the observation model parameters. |

extract_parameter_names | Extract the names of all the model parameters in the fit... |

extract_parameters | Extract the estimates of the model parameters (observation,... |

extract_quantity | Extract estimated quantities from fit objects. |

extract_R | Extract the dimension of the observation vector _R_. |

extract_seed | Extract the time elapsed when fitting the model. |

extract_spec | Extract the specification object used to fit the model... |

extract_T | Extract the length of the time series _T_. |

extract_time | Extract the time elapsed when fitting the model. |

extract_y | Extract the obsevation matrix used to fit the model _y_. |

extract_ypred | Extract the sample of the observation variable drawn from the... |

extract_ysim | Extract the simulated sample of the observation variable... |

extract_zpred | Extract the sample of the hidden state path drawn from the... |

extract_zstar | Extract the estimates of the most likely hidden state... |

fit | Fit a model by MCMC |

get_current_theme | Return the current theme. |

get_default_theme | Return the default theme. |

get_plot_theme | Return the current theme for visualizations. |

get_print_settings | Return the current theme for text printouts. |

hmm | Specify a Hidden Markov Model |

is.stanfit | Check if it is an object created by 'sampling'. |

is.stanoptim | Verify that the object was created by 'optimizing'. |

load_theme | Loads a theme into the R session. |

make_text_header | Make a string with a header. |

make_text_line | Make a string with a line (horizontal rule). |

make_text_subheader | Make a string with a subheader. |

mixture | Specify a mixture model |

optimizing | Fit a model by MAP |

optimizing_all | Run several instances of the optimization algorithm. |

optimizing_best | Run several instances of the optimization algorithm. |

optimizing_run | Run one instance of the |

plot_ppredictive | Plot samples drawn from the posterior predictive density. |

plot_series | Plot the observation series along with many other... |

plot_state_probability | Plot the estimated hidden path along with many other... |

run | Run a Markov-chain Monte Carlo algorithm to sample from the... |

sampling | Draw samples from a specification. |

select_all_parameters | Return the name of all model parameters. |

select_initial_parameters | Return the name of the initial model parameters. |

select_obs_parameters | Return the name of the observation model parameters. |

select_parameters | Return the name of the model parameters. |

select_transition_parameters | Return the name of the transition model parameters. |

sim | Simulate data from the prior predictive density. |

specify | Specify a model. |

theme | Theme for BayesHMM visualizations and printouts |

validate_calibration | Validate a model via a procedure based on simulated data. |

zzz | Prologue |

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