Man pages for bayesdfa
Bayesian Dynamic Factor Analysis (DFA) with 'Stan'
| bayesdfa-package | The 'bayesdfa' package. |
| dfa_cv | Apply cross validation to DFA model |
| dfa_fitted | Get the fitted values from a DFA as a data frame |
| dfa_loadings | Get the loadings from a DFA as a data frame |
| dfa_trends | Get the trends from a DFA as a data frame |
| find_dfa_trends | Find the best number of trends according to LOOIC |
| find_inverted_chains | Find which chains to invert |
| find_regimes | Fit multiple models with differing numbers of regimes to... |
| find_swans | Find outlying "black swan" jumps in trends |
| fit_dfa | Fit a Bayesian DFA |
| fit_regimes | Fit models with differing numbers of regimes to trend data |
| hmm_init | Create initial values for the HMM model. |
| invert_chains | Invert chains |
| is_converged | Summarize Rhat convergence statistics across parameters |
| loo | LOO information criteria |
| plot_fitted | Plot the fitted values from a DFA |
| plot_loadings | Plot the loadings from a DFA |
| plot_regime_model | Plot the state probabilities from 'find_regimes()' |
| plot_trends | Plot the trends from a DFA |
| predicted | Calculate predicted value from DFA object |
| rotate_trends | Rotate the trends from a DFA |
| sim_dfa | Simulate from a DFA |
| trend_cor | Estimate the correlation between a DFA trend and some other... |
