Man pages for echoice2
Choice Models with Economic Foundation
| dd_dem | Discrete Choice Predictions (HMNL) |
| dd_dem_sr | Discrete Choice Predictions (HMNL with attribute-based... |
| dd_est_hmnl | Estimate discrete choice model (HMNL) |
| dd_est_hmnl_screen | Estimate discrete choice model (HMNL, attribute-based... |
| dd_LL | Log-Likelihood for compensatory hmnl model |
| dd_LL_sr | Log-Likelihood for screening hmnl model |
| dummify | Create dummy variables within a tibble |
| dummyvar | Dummy-code a categorical variable |
| ec_boxplot_MU | Generate MU_theta boxplot |
| ec_boxplot_screen | Generate Screening probability boxplot |
| ec_dem_aggregate | Aggregate posterior draws of demand |
| ec_demcurve | Create demand curves |
| ec_demcurve_cond_dem | Create demand-incidence curves |
| ec_demcurve_inci | Create demand-incidence curves |
| ec_dem_eval | Evaluate (hold-out) demand predictions |
| ec_dem_summarise | Summarize posterior draws of demand |
| ec_draws_MU | Obtain MU_theta draws |
| ec_draws_screen | Obtain Screening probability draws |
| ec_estimates_MU | Obtain upper level model estimates |
| ec_estimates_screen | Summarize attribute-based screening parameters |
| ec_estimates_SIGMA | Obtain posterior mean estimates of upper level covariance |
| ec_estimates_SIGMA_corr | Obtain posterior mean estimates of upper level correlations |
| ec_gen_err_ev1 | Simulate error realization from EV1 distribution |
| ec_gen_err_normal | Simulate error realization from Normal distribution |
| echoice2-package | echoice2: Choice Models with Economic Foundation |
| ec_lmd_NR | Obtain Log Marginal Density from draw objects |
| ec_lol_tidy1 | Convert "list of lists" format to long "tidy" format |
| ec_screenprob_sr | Screening probabilities of choice alternatives |
| ec_screen_summarise | Summarize posterior draws of screening |
| ec_summarize_attrlvls | Summarize attributes and levels |
| ec_trace_MU | Generate MU_theta traceplot |
| ec_trace_screen | Generate Screening probability traceplots |
| ec_undummy | Converts a set of dummy variables into a single categorical... |
| ec_undummy_lowhigh | Convert dummy-coded variables to low/high factor |
| ec_undummy_lowmediumhigh | Convert dummy-coded variables to low/medium/high factor |
| ec_undummy_yesno | Convert dummy-coded variables to yes/no factor |
| ec_util_choice_to_long | Convert a vector of choices to long format |
| ec_util_dummy_mutualeclusive | Find mutually exclusive columns |
| get_attr_lvl | Obtain attributes and levels from tidy choice data with... |
| grapes-.-grapes | Get the attribute of an object |
| icecream | icecream |
| icecream_discrete | icecream_discrete |
| logMargDenNRu | Log Marginal Density (Newton-Raftery) |
| pizza | pizza |
| prep_newprediction | Match factor levels between two datasets |
| vd_add_prodid | Add product id to demand draws |
| vd_dem_summarise | Summarize posterior draws of demand (volumetric models only) |
| vd_dem_vdm | Demand Prediction (Volumetric Demand Model) |
| vd_dem_vdm_screen | Demand Prediction (Volumetric demand, attribute-based... |
| vd_dem_vdm_ss | Demand Prediction (Volumetric demand, accounting for set-size... |
| vd_est_vdm | Estimate volumetric demand model |
| vd_est_vdm_screen | Estimate volumetric demand model with attribute-based... |
| vd_est_vdm_ss | Estimate volumetric demand model accounting for set size... |
| vd_LL_vdm | Log-Likelihood for compensatory volumetric demand model |
| vd_LL_vdm_screen | Log-Likelihood for conjunctive-screening volumetric demand... |
| vd_LL_vdmss | Log-Likelihood for volumetric demand model with set-size... |
| vd_long_tidy | Generate tidy choice data with dummies from long-format... |
| vd_prepare | Prepare choice data for analysis |
| vd_prepare_nox | Prepare choice data for analysis (without x being present) |
| vd_thin_draw | Thin 'echoice2'-vd draw objects |
