| as_cov_names | Re-label alternative specific covariates |
| check_form | Check model formula |
| check_prior | Check prior parameters |
| choice_probabilities | Compute choice probabilities |
| classification | Preference-based classification of deciders |
| coef.RprobitB_fit | Extract model effects |
| compute_p_si | Compute choice probabilities at posterior samples |
| cov_mix | Extract estimated covariance matrix of mixing distribution |
| create_lagged_cov | Create lagged choice covariates |
| d_to_gamma | Transform increments to thresholds |
| fit_model | Fit probit model to choice data |
| get_cov | Extract covariates of choice occasion |
| gibbs_sampler | Gibbs sampler for probit models |
| ll_ordered | Compute ordered probit log-likelihood |
| mml | Approximate marginal model likelihood |
| model_selection | Compare fitted models |
| mode_approx | Gibbs sample mode |
| npar | Extract number of model parameters |
| npar.RprobitB_fit | Extract number of model parameters |
| overview_effects | Print effect overview |
| plot.RprobitB_coef | Extract model effects |
| plot.RprobitB_fit | Visualize fitted probit model |
| plot.RprobitB_mml | Approximate marginal model likelihood |
| plot_class_allocation | Plot class allocation (for 'P_r = 2' only) |
| plot_mixture_contour | Plot bivariate contour of mixing distributions |
| plot_roc | Plot ROC curve |
| point_estimates | Compute point estimates |
| predict.RprobitB_fit | Predict choices |
| pred_acc | Compute prediction accuracy |
| prepare_data | Prepare choice data for estimation |
| print.RprobitB_coef | Extract model effects |
| print.RprobitB_mml | Approximate marginal model likelihood |
| print.RprobitB_model_selection | Compare fitted models |
| print.RprobitB_parameter | Define probit model parameter |
| RprobitB_parameter | Define probit model parameter |
| R_hat | Compute Gelman-Rubin statistic |
| sample_allocation | Sample allocation |
| simulate_choices | Simulate choice data |
| train_choice | Stated Preferences for Train Traveling |
| train_test | Split choice data into train and test subset |
| transform.RprobitB_fit | Transform fitted probit model |
| update.RprobitB_fit | Update and re-fit probit model |
| update_b | Update class means |
| update_b_c | Update mean of a single class |
| update_classes_dp | Dirichlet process class updates |
| update_classes_wb | Weight-based class updates |
| update_coefficient | Update coefficient vector |
| update_d | Update utility threshold increments |
| update_m | Update class sizes |
| update_Omega | Update class covariances |
| update_Omega_c | Update covariance of a single class |
| update_s | Update class weight vector |
| update_Sigma | Update error covariance matrix |
| update_U | Update utility vector |
| update_U_ranked | Update ranked utility vector |
| update_z | Update class allocation vector |